• Journal of Sensor Science and Technology
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• v.24 no.5
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• pp.281-286
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• 2015

The importance of air quality monitoring is rapidly increasing. Even though state-of-the-art air quality monitoring technologies such as mass spectrometry, gas chromatography, and optical measurement enable high-fidelity measurement of air pollutants, they cannot be widely used for portable or personalized platforms because of their high cost and complexity. Recently, personalized and localized environmental monitoring, rather than global and averaged environmental monitoring, has drawn greater attention with the advancement of mobile telecommunication technologies. Here, micro- and nano-technologies enable highly integrated and ultra-compact sensors to meet the needs of personalized environmental monitoring. In this paper, several examples of MEMS-based gas sensors for compact and personalized air quality monitoring are explained. Additionally, the principles and usage of functional nanomaterials are discussed for highly sensitive and selective gas sensors.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.297-303
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• 2023

Pediatric Computed Tomography (CT) examinations can often result in exam failures or the need for frequent retests due to the difficulty of cooperation from young patients. Deep Learning Image Reconstruction (DLIR) methods offer the potential to obtain diagnostically valuable images while reducing the retest rate in CT examinations of pediatric patients with high radiation sensitivity. In this study, we investigated the possibility of applying DLIR to reduce artifacts caused by respiration or motion and obtain clinically useful images in pediatric chest CT examinations. Retrospective analysis was conducted on chest CT examination data of 43 children under the age of 7 from P Hospital in Gyeongsangnam-do. The images reconstructed using Filtered Back Projection (FBP), Adaptive Statistical Iterative Reconstruction (ASIR-50), and the deep learning algorithm TrueFidelity-Middle (TF-M) were compared. Regions of interest (ROI) were drawn on the right ascending aorta (AA) and back muscle (BM) in contrast-enhanced chest images, and noise (standard deviation, SD) was measured using Hounsfield units (HU) in each image. Statistical analysis was performed using SPSS (ver. 22.0), analyzing the mean values of the three measurements with one-way analysis of variance (ANOVA). The results showed that the SD values for AA were FBP=25.65±3.75, ASIR-50=19.08±3.93, and TF-M=17.05±4.45 (F=66.72, p=0.00), while the SD values for BM were FBP=26.64±3.81, ASIR-50=19.19±3.37, and TF-M=19.87±4.25 (F=49.54, p=0.00). Post-hoc tests revealed significant differences among the three groups. DLIR using TF-M demonstrated significantly lower noise values compared to conventional reconstruction methods. Therefore, the application of the deep learning algorithm TrueFidelity-Middle (TF-M) is expected to be clinically valuable in pediatric chest CT examinations by reducing the degradation of image quality caused by respiration or motion.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1999.06a
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• pp.359-365
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• 1999

We have evaluated the performance and some physical properties of 25 automotive engine oils (21 domestic and 5 imported products) which are purchased on the market to verify the API(American Petroleum Institute) or ILSAC(International Lubricant Standardization and Approval Committee) certification marks attached on the products and to determine the necessity of the quality control of the engine oils on the market. 12 test items are chosen according to API engine oil specification, which are flash point, pour point, cold cranking simulator apparent viscosity, pumping viscosity, gelation index, HTHS(High Temperature High Shear viscosity), foam, high temperature foam, filterability, volatility, high temperature deposit(TEOST), phosphorus content. We have found one product which did not meet the API specification on gelation index, one on HTHS, four on foam, and one on volatility, which implies that the quality control system is in need to check the fidelity of the certification marks attached on the engine oils being marketed. In addition, this works raises the necessity of the upgrade of the present Korean engine oil specification.

• Korean Journal of Cognitive Science
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• v.23 no.4
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• pp.517-551
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• 2012

We are imitating animals. True imitation can be defined as a learning to do an act from seeing it done by others. We have been building culture by imitating others' skills and knowledge with high fidelity. In this regard, it is important to ask how the faculty of imitation has evolved and how imitation behaviors develop ontogenetically. It is also interesting to see whether nonhuman animals can imitate truly or not and how different imitation learning is among human and non-human animals. In this paper, first I review empirical data from imitation studies with human and nonhuman animals. Comparing different species, I highlight their different levels of copying fidelity and explain the reason why they are showing the difference. Then I review recent studies on neurobiological mechanisms underlying imitation. The initial neurobiological studies on imitation in humans suggested a core imitation circuitry composed of mirror neuron system [inferior parietal lobule(IPL) and inferior frontal gyrus(IFG)] and the posterior part of the superior temporal sulcus(pSTS). More recent studies on the neurobiology of imitation, however, has gone beyond the studies on the core mechanisms. Finally, I try to find out implications of psychology and biology of imitation for cultural evolution. I argue for a memetic approach to cultural evolution, along the lines with a recent study on measuring memes by mirror neurons system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.272-278
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• 2015

This paper analyzed interference impact between wireless headset and Wireless Fidelity which get a high possibility of simultaneously operating in the Industry Science Medical(ISM) bands. Analysis methods of Minimum Coupling Loss(MCL) and Monte Carlo(MC) were applied by using the characters and parameters referenced to Institute of Electrical and Electronic Engineers(IEEE) 802.11b. The protection distance between interferer (WiFi transmitter) and victim (Wireless headset receiver) was calculated through the MCL. The protection distance was obtained for the case of single interferer, and the maximum allowable number of multiple interferers was computed according to the cell radius of a victim system to meet 5 % below of interference probability by using a statistical analysis based on the MC method. The analysis results are expected to be used as a guideline to coexist the wireless headset and low power devices in the ISM band.

• Nuclear Engineering and Technology
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• v.52 no.2
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• pp.287-295
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• 2020

Group method of data handling (GMDH) is considered one of the earliest deep learning methods. Deep learning gained additional interest in today's applications due to its capability to handle complex and high dimensional problems. In this study, multi-layer GMDH networks are used to perform uncertainty quantification (UQ) and sensitivity analysis (SA) of nuclear reactor simulations. GMDH is utilized as a surrogate/metamodel to replace high fidelity computer models with cheap-to-evaluate surrogate models, which facilitate UQ and SA tasks (e.g. variance decomposition, uncertainty propagation, etc.). GMDH performance is validated through two UQ applications in reactor simulations: (1) low dimensional input space (two-phase flow in a reactor channel), and (2) high dimensional space (8-group homogenized cross-sections). In both applications, GMDH networks show very good performance with small mean absolute and squared errors as well as high accuracy in capturing the target variance. GMDH is utilized afterward to perform UQ tasks such as variance decomposition through Sobol indices, and GMDH-based uncertainty propagation with large number of samples. GMDH performance is also compared to other surrogates including Gaussian processes and polynomial chaos expansions. The comparison shows that GMDH has competitive performance with the other methods for the low dimensional problem, and reliable performance for the high dimensional problem.

• Korean Journal of Health Education and Promotion
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• v.24 no.5
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• pp.1-21
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• 2007

Adolescent psychosocial smoking prevention programs have been successful, but limited in the magnitude of program effects. The present study is the secondary analysis after the previous study estimated mean effect sizes in smoking knowledge, attitudes, skills, and behaviors with treatment variables. Regardless of overall program effect estimations that other meta.analysis studies have done, this study is conducted to identify explanatory variables that are likely to increase program effects. A decrease of adolescent smoking behaviors is associated with the following factors: a. Younger students ($5^{th}-7^{th}$) than older students ($8^{th}-12^{th}$). b. Research methodology using true experimental design, quasi experimental design with equivalence between groups, use of random assignment, 10% or less attrition rate, use of a no treatment control group, high implementation fidelity, and/or acceptable instrumentation reliability. c. Programs using trained peer leaders, targeting cigarette smoking only, implementing 10 or more treatment sessions and/ or providing booster sessions.

• BMB Reports
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• v.37 no.3
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• pp.269-274
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• 2004

DNA polymerases without the 3' exonuclease function ($exo^-$ pol) have been widely used in sequencing and SNP genotyping. As a major player that expedited the coming of the postgenomic era, $exo^-$ polymerases worked remarkably well in the Human Genome Sequencing Project. However, it has become a challenge for this class of polymerases to efficiently screen the large number of SNPs that are found in the human genome. For more than three decades it has been recognized that polymerase fidelity varied according to the presence of proofreading activity that is mediated by its internal 3' exonuclease. Polymerases with proofreading function are famous for their high fidelity in DNA replication both in vivo and in vitro, but this well-known class of polymerases has been almost completely neglected in genetic analysis in the postgenomic era. We speculate that $exo^+$ polymerases may exhibit higher nucleotide identification ability when compared to $exo^-$ polymerases for an in vitro genetic analysis. With the application of $exo^+$ polymerases in SNP assays, a novel mechanism for the maintenance of DNA replication, the on/off switch, was discovered. Two new SNP assays have been developed to carry out genome-wide genotyping, taking advantage of the enzymatic properties of $exo^+$ polymerases. Furthermore, the on/off switch mechanism embodies a powerful nucleotide identification ability, which can be used to discriminate the bases that are upstream of the 3' terminus, and thus defines a new concept in de novo sequencing technology. Application of $exo^+$ polymerases to genetic analysis, and especially SNP assays, will greatly accelerate the pace to personalized medicine.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.10
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• pp.823-832
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• 2018

In general, the fidelity of the aircraft dynamic model is verified by comparison with the flight test results of the target aircraft. Therefore, the reference flight data for performance comparisons must be extracted. This process requires a lot of time and manpower to extract useful data from the vast quantity of flight test data containing various noise for comparing fidelity. In particular, processing of flight data is complex because rotorcraft have high non-linearity characteristics such as coupling and wake interference effect and perform various maneuvers such as hover and backward flight. This study defines flight data processing criteria for rotorcraft and provides procedures and methods for automated processing of static and dynamic flight data using data mining techniques. Finally, the methods presented are validated using flight data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1074-1081
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• 2021

It has recently been noticed that the headway of unlicensed wireless technology is necessary as user's demands of wireless tech increase and the development of high-speed data service by using low-power short-range wireless network is needed. Hence, it is inevitable to study sharing and coexistence for broadband spectrum of diverse unlicensed application with wide bandwidth. In this paper, an interference examination between unlicensed WiFi (Wireless Fidelity) in the 6GHz and OB (Outside Broadcasting) system which is an incumbent service in the same frequency band was conducted and it suggests separation distance for the coexistence. Thus, MCL (Minimum Coupling Loss) and MC (Monte Carlo) methods were used to set up interference scenarios for the interference analysis and compute the separation distance between two systems according to the same frequency band and frequency separation.