• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.6
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• pp.60-65
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• 2021

In this paper, we examined the ignition possibility of the propellant depending on its non-uniform composition of aluminum. Impact and friction sensitivity was investigated by arbitrarily changing the aluminum content in the range of 14~20% to simulate the non-uniform distribution of aluminum in the propellant. As a result of measuring the impact sensitivity, the 50% ignition energy and minimum ignition energy have values around 50 J regardless of the aluminum content. This means that the propellant does not become sensitive to impact even if the aluminum content is increased. On the other hand, the friction sensitivity result shows that as the aluminum content increases, the 50% ignition force and minimum ignition forces were decreased, and thus the propellant becomes sensitive. "Hot Spot" model of propellant ignition is applied, the space inside the propellant is momentarily compressed and ignited by friction stimuli rather than by impact stimuli.

• Journal of the Korea Society for Simulation
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• v.18 no.2
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• pp.65-75
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• 2009

The semiconductor manufacturing process normally includes a great number of complex sequential steps those are related with various types of equipment. Such equipments are installed with the mixed patterns of serial or parallel structures while considering a number of engineering or environmental factors at the same time. It is thus extremely difficult to change the layout after installation due to expensive costs and other related factors. Because of these reasons, a new investment or layout change, which is usually caused by the production policy such as product mix or production quantity, must be carefully considered. This case study introduces a simulation conducted in a semiconductor parts production company which produces the Board on Chip (BOC)-type of packaging substrate and has plans to change the facility layout. For this study, we used $QUEST^{(R)}$ for simulation modeling and evaluated various strategies which may cause layout changes. Further, the Analytic Hierarchy Process (AHP) is applied to select the best strategy from several alternatives with multiple decision criteria.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.252-258
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• 2022

In this study, we propose a method for analyzing students' understanding of probability and statistics in small lectures at universities. A computer-based test for probability and statistics was performed on 95 science and engineering college students. After dividing the students' responses into 7 clusters using the Robust PCA and the Gaussian mixture model, the achievement of each subject was analyzed for each cluster. High-ranking clusters generally showed high achievement on most topics except for statistical estimation, and low-achieving clusters showed strengths and weaknesses on different topics. Compared to the widely used PCA-based dimension reduction followed by clustering analysis, the proposed method showed each group's characteristics more clearly. The characteristics of each cluster can be used to develop an individualized learning strategy.

• Communications of Mathematical Education
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• v.37 no.2
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• pp.257-276
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• 2023

Mathematical modeling can be described as a series of processes in which real-world problem situations are understood, interpreted using mathematical methods, and solved based on mathematical models. The effectiveness of mathematics instruction using mathematical modeling has been demonstrated through prior research. This study aims to explore insights for mathematical modeling instruction by analyzing the metacognitive characteristics shown in the mathematical modeling cycle, according to the mathematical thinking styles of elementary math gifted students. To achieve this, a mathematical thinking style assessment was conducted with 39 elementary math gifted students from University-affiliated Science Gifted Education Center, and based on the assessment results, they were classified into visual, analytical, and mixed groups. The metacognition manifested during the process of mathematical modeling for each group was analyzed. The analysis results revealed that metacognitive elements varied depending on the phases of modeling cycle and their mathematical thinking styles. Based on these findings, didactical implications for mathematical modeling instruction were derived.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.313-316
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• 2021

In the IoT(IoT: Internet of Things) environment, network configuration is essential to collect data generated from objects. Various communication methods are used to process data of objects, and wireless communication methods such as Bluetooth and WiFi are mainly used. In order to collect data of objects, a communication module must be installed to collect data generated from sensors or edge devices in real time. And in order to deliver data to the database, a software architecture must be configured. Data generated from objects can be stored and managed in a database in real time, and data necessary for industrial safety can be extracted and utilized for industrial safety service applications. In this paper, a network environment was constructed using a LoRa(LoRa: Long Range) gateway to collect object data, and a client/server data collection model was designed to collect object data transmitted from the LoRa module. In order to secure the resources necessary for data collection and storage management without data leakage, data collection should be possible in real time. As an application service, location data required for industrial safety can be stored and managed in a database in real time.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.111-119
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• 2023

Recently, a variety of new cement-based materials have been developed, and attempts to predict the properties of these new materials are increasing. In this study, we aimed to predict the rheological properties of binary blended pastes. The cementitious materials used in the study included Portland cement (PC), fly ash (FA), blast furnace slag (BS), and silica fume (SF). The three binder components, fly ash, blast furnace slag, and silica fume, were blended with cement as the foundational composition. We predicted the yield stress and plastic viscosity of the pastes using the YODEL (Yield stress mODEL) and Krieger-Dougherty's equation. The predictive model's performance was validated by comparing it with experimental results obtained using a rheometer. When the rheological properties of the binary blended paste were predicted by reconstructing the properties and parameters used to predict the individual materials, it was evident that the predictions made using the proposed method closely matched the experimental results.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.401-404
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• 2003

In this paper, $H_2$, $H_{\infty}$, and mixed $H_2/H_{\infty}$ FIR filters are newly proposed for discrete-time state space signal models. The proposed filters require linearity, unbiased property, FIR structure, and independence of the initial state information in addition to the performance criteria in both $H_2$ and $H_{\infty}$ sense. It is shown that $H_2$, $H_{\infty}$, and mixed $H_2/H_{\infty}$ FIR filter design problems can be converted into convex programming problems via linear matrix inequalities (LMIs) with a linear equality constraint. Simulation studies illustrat that the proposed FIR filter is more robust against uncertainties and has faster convergence than the conventional IIR filters. the conventional IIR filters.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.888-896
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• 2023

When an aircraft is landing, it is expected that the aircraft will follow a specified approach procedure and then land at the airport. However, depending on the airport situation, neighbouring aircraft or the instructions of the air traffic controller, there can be a deviation from the specified approach. Detecting aircraft approach patterns is necessary for traffic flow and flight safety, and this paper suggests clustering techniques to identify aircraft patterns in the approach segment. The Gaussian Mixture Model (GMM), one of the machine learning techniques, is used to cluster the trajectories of aircraft, and ADS-B data from aircraft landing at the Gimhae airport in 2019 are used. The aircraft trajectories are clustered on the plane, and a total of 86 approach trajectory patterns are extracted using the centroid value of each cluster. Considering the correlation between the approach procedure pattern and overshoots, the distribution of overshoots is calculated.

• The Journal of the Acoustical Society of Korea
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• v.26 no.8
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• pp.390-396
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• 2007

In this letter, we propose a novel approach to improve the performance of speech/music classification for the selectable mode vocoder(SMV) of 3GPP2 using the Gaussian mixture model(GMM) which is based on the expectation-maximization(EM) algorithm. We first present an effective analysis of the features and the classification method adopted in the conventional SMV. And then feature vectors which are applied to the GMM are selected from relevant Parameters of the SMV for the efficient speech/music classification. The performance of the proposed algorithm is evaluated under various conditions and yields better results compared with the conventional scheme of the SMV.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.401-407
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• 2009

In this paper, we propose a novel method for the cross-correlation based double-talk detection (DTD), which employing the Gaussian Mixture Model (GMM) in the frequency domain. The proposed algorithm transforms the cross correlation coefficient used in the time domain into 16 channels in the frequency domain using the discrete fourier transform (DFT). The channels are then selected into seven feature vectors for GMM and we identify three different regions such as far-end, double-talk and near-end speech using the likelihood comparison based on those feature vectors. The presented DTD algorithm detects efficiently the double-talk regions without Voice Activity Detector which has been used in conventional cross correlation based double-talk detection. The performance of the proposed algorithm is evaluated under various conditions and yields better results compared with the conventional schemes. especially, show the robustness against detection errors resulting from the background noises or echo path change which one of the key issues in practical DTD.