• Aerospace Engineering and Technology
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• v.10 no.1
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• pp.107-115
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• 2011

The line-telemetry data processing system is necessary for monitoring the status of each onboard systems of KSLV-I upper stage during the ground tests and launch preparation. The mission of line-telemetry system is to provide reference telemetry data and to monitor the status of upper stage. The line-telemetry data processing system consists of a PCM acquisition/processing server, a system management server, and 9 monitoring consoles. In this paper, we will describe the overview of onboard remote measurement system, the design of the line-telemetry data processing system, anomaly setup information for indicating alarm signal in case of abnormal occurrence, and the result of the ground test and flight test.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.53-59
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• 2008

Recently, vision-based hand gesture recognition techniques have been developed for assisting elderly and disabled people to control home appliances. Frequently occurred problems which lower the hand gesture recognition rate are due to the inter-person variation and intra-person variation. The recognition difficulty caused by inter-person variation can be handled by using user dependent model and model selection technique. And the recognition difficulty caused by intra-person variation can be handled by using fuzzy logic. In this paper, we propose multivariate fuzzy decision tree learning and classification method for a hand motion recognition system for multiple users. When a user starts to use the system, the most appropriate recognition model is selected and used for the user.

• Korean Journal of Community Nutrition
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• v.27 no.4
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• pp.273-285
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• 2022

Objectives: This study compared the nutritional intakes of early and late preterm infants in a neonatal intensive care unit (NICU) and at home. The dietary problems and the need for community care services for premature infants were further investigated. Methods: This is a cross-sectional and descriptive study on 125 preterm infants and their parents (Early preterm n = 70, Late preterm n = 55). The data were collected by surveying the parents of preterm infants and from hospital medical records. Results: No significant differences were obtained between the early and late preterm infant groups when considering the proportion of feeding types in the NICU and at home. Early preterm infants were fed with a greater amount of additional calories at home and had more hours of tube feeding (P = 0.022). Most preterm infants had feeding problems. However, there was no significant difference between early and late preterm infants in the mental pain of parents, sleeping, feeding, and weaning problems at home. Many parents of preterm babies had no external support, and more than half the parents required community care to take care of their preterm babies. Conclusions: Regardless of the gestational age, most preterm infants have several problems with dietary intake. Our study indicates the need to establish community care services for preterm infants.

• Smart Media Journal
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• v.11 no.2
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• pp.31-38
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• 2022

Promptly predicting changes in the salinity in rivers is an important task to predict the damage to agriculture and ecosystems caused by salinity infiltration and to establish disaster prevention measures. Because machine learning(ML) methods show much less computation cost than physics-based hydraulic models, they can predict the river salinity in a relatively short time. Due to shorter training time, ML methods have been studied as a complementary technique to physics-based hydraulic model. Many studies on salinity prediction based on machine learning have been studied actively around the world, but there are few studies in South Korea. With a massive number of datasets available publicly, we evaluated the performance of various kinds of machine learning techniques that predict the salinity of the Nakdong River Estuary Basin. As a result, LightGBM algorithm shows average 0.37 in RMSE as prediction performance and 2-20 times faster learning speed than other algorithms. This indicates that machine learning techniques can be applied to predict the salinity of rivers in Korea.

• Journal of the Korea Society for Simulation
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• v.33 no.2
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• pp.27-35
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• 2024

We aimed to shed light on the issue of perpetuating societal disparities by analyzing the impact of inherent biases present in datasets used for training artificial intelligence models on the predictions generated by Artificial Intelligence(AI). Therefore, to examine the influence of data bias on AI models, we constructed an original dataset containing biases related to gender wage gaps and subsequently created a de-identified dataset. Additionally, by utilizing the decision tree algorithm, we compared the outputs of AI models trained on both the original and de-identified datasets, aiming to analyze how data de-identification affects the biases in the results produced by artificial intelligence models. Through this, our goal was to highlight the significant role of data de-identification not only in safeguarding individual privacy but also in addressing biases within the data.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.5
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• pp.593-598
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• 2015

Non-linear cellular automata is difficult to analyze mathematically than linear cellular automata. So it is difficult to identify reachable states and attractors of nongroup non-linear cellular automata than nongroup linear cellular automata. In this paper, we propose a new reachable table to overcome these problems. We can see the next state for all the states of the non-linear cellular automata by the proposed reachable table. In addition, we can identify reachable states and attractors by the reachable table.

• Journal of Korea Multimedia Society
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• v.14 no.10
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• pp.1323-1334
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• 2011

This paper suggests the border based HSFI algorithm to hide sensitive frequent itemsets. Node formation of FP-Tree which is different from the previous one uses the border to minimize the impacts of nonsensitive frequent itemsets in hiding process, including the organization of sensitive and border information, and all transaction as well. As a result of applying HSFI algorithms, it is possible to be the example transaction database, by significantly reducing the lost items, it turns out that HSFI algorithm is more effective than the existing algorithm for maintaining the quality of more improved database.

• Journal of the Korean Ceramic Society
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• v.46 no.5
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• pp.441-446
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• 2009

Dense crack-free yttria film with 10 $\mu m$ thickness was prepared on aluminum by aerosol deposition. X-ray diffraction pattern on the film showed that it contained the same crystalline phase as the raw powder. Transmission electron microscopy revealed a nanostructured yttria film with grains smaller than 100 nm. Tensile adhesion strength between the film and aluminum substrate was 57.8 $\pm$ 6.3MPa. According to the etching test with $CF_4-O_2$ plasma, the etching rate of the yttria film was 1/100 that of quartz, 1/10 that of sintered alumina and comparable to that of sintered yttria.

• The Journal of Korean Association of Computer Education
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• v.10 no.6
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• pp.1-10
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• 2007

Programming is emphasized in information(computer science) education course domestically and in foreign countries, and novices are given ample opportunities to experience programming. Programming error is a critical factor which makes it difficult to learn programming for novices. However, if they are given appropriate feedback, it can have positive influence on programming learning. In this paper, we design programming learning supporting system for novice through error feedback and provide some implementations for EPL 'Dolittle'. This system has four features as highlighting, guiding messages, object tree, and step-execution.

• Textile Coloration and Finishing
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• v.32 no.3
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• pp.158-166
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• 2020

Self-cleaning fabric is a fabric having a function of decotamination via photodecomposition of photocatalyst or wash-off of contaminants on the superhydrophobic surface. TiO₂ is the main photocatalyst for this purpose, but it only functions under UV light which is only a little portion of sunlight, compared to visible light. In this regard, this study aims to investigate Fe-doped TiO₂ for improved photodecomposition from visible light sensitization to apply self-cleaning finishing of PET fabrics. Moreover, the Fe-doped TiO₂ treated PET fabric was further treated with hexadecyltrimethoxysilane to provide superhydrophobicity on the PET fabrics. As a result of this dual treatment, the prepared fabric exhibited excellent photodecomposition of methylene blue with 96.96% in 12h under sunlight and superhydrophobicity with water contact angle of 166.5° and roll-off angle of 7°. This suggested that the excellent self-cleaning functions can be privided to PET fabric via Fe-doped TiO₂ and hexadecyltrimethoxysilane treatment.