• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.419-427
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• 2024

This study assessed the potential impact of gas leakage resulting from accidental damage to buried urban gas pipelines during perforating operation near subway construction sites. The risk of explosions due to ignition sources such as static electricity, arising from gas infiltrating the subway construction site through storm sewers and sewage pipes, was evaluated using the ALOHA program. The results of the threat zone calculation, which input various parameters of urban gas pipelines such as length, diameter, and pressure, indicated that the flammable area within the vapor cloud extended from 1.2 to 1.4 km (red zone), the blast area ranged from 0.8 to 1.0 km (yellow zone), and the jet fire extended from 45 to 61 m (red zone). This study demonstrates that within the flammable area of the vapor cloud, a specific combination of concentration and conditions can increase flammability. The blast area may experience explosions with a pressure of 1.0 psi, sufficient to break glass windows. In the event of a jet fire, high temperatures and intense radiant heat exposure lead to rapid fire propagation in densely populated areas, posing a high risk of casualties. The findings are presented in terms of the sphere of influence and threat zone ranges.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.2
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• pp.28-35
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• 2024

Corrosion inside electronic packages significantly impacts the system performance and reliability, necessitating non-destructive diagnostic techniques for system health management. This study aims to present a non-destructive method for assessing corrosion in copper interconnects using the Smith chart, a tool that integrates the magnitude and phase of complex impedance for visualization. For the experiment, specimens simulating copper transmission lines were subjected to temperature and humidity cycles according to the MIL-STD-810G standard to induce corrosion. The corrosion level of the specimen was quantitatively assessed and labeled based on color changes in the R channel. S-parameters and Smith charts with progressing corrosion stages showed unique patterns corresponding to five levels of corrosion, confirming the effectiveness of the Smith chart as a tool for corrosion assessment. Furthermore, by employing data augmentation, 4,444 Smith charts representing various corrosion levels were obtained, and artificial intelligence models were trained to output the corrosion stages of copper interconnects based on the input Smith charts. Among image classification-specialized CNN and Transformer models, the ConvNeXt model achieved the highest diagnostic performance with an accuracy of 89.4%. When diagnosing the corrosion using the Smith chart, it is possible to perform a non-destructive evaluation using electronic signals. Additionally, by integrating and visualizing signal magnitude and phase information, it is expected to perform an intuitive and noise-robust diagnosis.

• Journal of the Korean earth science society
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• v.45 no.3
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• pp.173-191
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• 2024

Typhoons are significant meteorological phenomena that cause interactions among the ocean, atmosphere, and land within Earth's system. In particular, wind speed, a key characteristic of typhoons, is influenced by various factors such as central pressure, trajectory, and sea surface temperature. Therefore, a comprehensive understanding based on actual observational data is essential. In the 2015 revised secondary school textbooks, typhoon wind speed is presented through text and illustrations; hence, exploratory activities that promote a deeper understanding of wind speed are necessary. In this study, we developed a data visualization program with a graphical user interface (GUI) to facilitate the understanding of typhoon wind speeds with simple operations during the teaching-learning process. The program utilizes red-green-blue (RGB) image data of Typhoons Mawar, Guchol, and Bolaven -which occurred in 2023- from the Korean geostationary satellite GEO-KOMPSAT-2A (GK-2A) as the input data. The program is designed to calculate typhoon wind speeds by inputting cloud movement coordinates around the typhoon and visualizes the wind speed distribution by inputting parameters such as central pressure, storm radius, and maximum wind speed. The GUI-based program developed in this study can be applied to typhoons observed by GK-2A without errors and enables scientific exploration based on actual observations beyond the limitations of textbooks. This allows students and teachers to collect, process, analyze, and visualize real observational data without needing a paid program or professional coding knowledge. This approach is expected to foster digital literacy, an essential competency for the future.

• Journal of the Korean Geotechnical Society
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• v.40 no.4
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• pp.49-60
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• 2024

Ground-penetrating radar (GPR) enables rapid data acquisition over extensive areas, but interpreting the obtained data requires specialized knowledge. Numerous studies have utilized numerical analysis methods to examine GPR signal characteristics under various conditions. To develop more realistic numerical models, the heterogeneous nature of the ground, which causes clutter, must be considered. Clutter refers to signals reflected by objects other than the target. The Peplinski material model and fractal techniques can simulate these heterogeneous characteristics, yet there is a shortage of research on the necessary input parameters. Moreover, methods for quantitatively evaluating the similarity between field and analytical data are not well established. In this study, we calculated the autocorrelation coefficient of field data and determined the correlation length using the autocorrelation function. The correlation length represented the temporal or spatial distance over which data exhibited similarity. By comparing the correlation length of field data with that of the numerical model incorporating fractal weights, we quantitatively evaluated a numerical model for heterogeneous ground. Consequently, the results of this study demonstrated a numerical modeling technique that reflected the clutter characteristics of the field through correlation length.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.67-76
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• 2024

Various types of assistive devices have been developed for upper limb amputees over the years, with myoelectric prosthesis particularly aimed at improving user convenience by enabling a range of hand gestures beyond simple grasping, tailored to the size and shape of objects. In this study, we developed a five-finger myoelectric prosthesis mimicking human hand size and finger movements, utilizing motor and worm gear mechanisms for stable and independent operation. Based on this, we designed a control system for independent finger control through electromyographic signal input, proposed a state transition-based hand gesture conversion algorithm by selecting representative eight hand gestures and defining conversion condition parameters. We introduced training and usability evaluation methods, and conducted usability assessments among upper limb amputees using dedicated tools, confirming the potential for commercial application of the algorithm and observing adaptive capabilities and high performance through iterative evaluations.

• Journal of the Korean GEO-environmental Society
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• v.13 no.5
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• pp.5-12
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• 2012

Antibiotics have been considered emerging compounds due to their continuous input and persistence in environment. Due to the limited biodegradability and widespread use of these antibiotics, an incomplete removal is attained in conventional wastewater treatment plants and relative large quantities are released into the environment. In this study, it was determined the adsorption and photocatalysis kinetics of antibiotics (Sulfamethoxazole, SMX) with various catalyst (Titanium dioxide; $TiO_2$, Hydroxyapatite; HAP) conditions under UV/$TiO_2$/HAP system. In addition, the statistical analysis of response surface methods (RSM) was used to determine the effects of operating parameters on UV/$TiO_2$/HAP system. $TiO_2$/HAP adsorbent were found to follow the pseudo second order reaction in the adsorption. In the result of applied intrapaticle diffusion model, the constants of reaction rate were $TiO_2$=$0.064min^{-1}$, HAP=$0.2866min^{-1}$ and $TiO_2$/HAP=$0.3708min^{-1}$, respectively.The result of RSM, term of regression analysis in analysis of variance (ANOVA) showed significantly p-value (p<0.05) and high coefficients for determination values($R^2$=96.2%, $R^2_{Adj}$=89.3%) that allowed satisfactory prediction of second order regression model. And the estimated optimal conditions for Y(Sulfamethoxazole removal efficiency, %) were $x_1$(initial concentration of Sulfamethoxazole)=-0.7828, $x_2$(amount of catalyst)=0.9974 and $x_3$(reation time)=0.5738 by coded parameters, respectively. According to the result of intraparticle diffusion model and photocatalysis experiments, it was shown that the $TiO_2$/HAP was more effective system than conventional AOPs(advanced oxidation processes, UV/$TiO_2$ system).

• ALGAE
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• v.32 no.2
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• pp.101-130
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• 2017

The ichthyotoxic Cochlodinium polykrikoides red tides have caused great economic losses in the aquaculture industry in the waters of Korea and other countries. Predicting outbreak of C. polykrikoides red tides 1-2 weeks in advance is a critical step in minimizing losses. In the South Sea of Korea, large C. polykrikoides red tide patches have often been recorded offshore and transported to nearshore waters. To explore the processes of offshore C. polykrikoides red tides, temporal variations in 3-dimensional (3-D) distributions of red tide organisms and environmental parameters were investigated by analyzing 4,432 water samples collected from 2-5 depths of 60 stations in the South Sea, Korea 16 times from May to Nov, 2014. In the study area, the vegetative cells of C. polykrikoides were found as early as May 7, but C. polykrikoides red tide patches were observed from Aug 21 until Oct 9. Cochlodinium red tides occurred in both inner and outer stations. Prior to the occurrence of large C. polykrikoides red tides, the phototrophic dinoflagellates Prorocentrum donghaiense (Jun 12 to Jul 11), Ceratium furca (Jul 11 to Aug 21), and Alexandrium fraterculus (Aug 21) formed red tides in sequence, and diatom red tides formed 2-3 times without a certain distinct pattern. The temperature for the optimal growth of these four red tide dinoflagellates is known to be similar. Thus, the sequence of the maximum growth rates of P. donghaiense > C. furca > A. fraterculus > C. polykrikoides may be partially responsible for this sequence of red tides in the inner stations following high nutrients input in the surface waters because of heavy rains. Furthermore, Cochlodinium red tides formed and persisted at the outer stations when $NO_3$ concentrations of the surface waters were < $2{\mu}M$ and thermocline depths were >20 m with the retreat of deep cold waters, and the abundance of the competing red-tide species was relatively low. The sequence of the maximum swimming speeds and thus potential reachable depths of C. polykrikoides > A. fraterculus > C. furca > P. donghaiense may be responsible for the large C. polykrikoides red tides after the small blooms of the other dinoflagellates. Thus, C. polykrikoides is likely to outgrow over the competitors at the outer stations by descending to depths >20 m and taking nutrients up from deep cold waters. Thus, to predict the process of Cochlodinium red tides in the study area, temporal variations in 3-D distributions of red tide organisms and environmental parameters showing major nutrient sources, formation and depth of thermoclines, intrusion and retreat of deep cold waters, and the abundance of competing red tide species should be well understood.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.4
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• pp.41-54
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• 2002

In this study, we have analyzed the effects of the membrane layer and the bragg reflector layers on the resonance characteristics through comparing the characteristics of the membrane type FBAR (Film Bulk Acoustic Wave Resonator) and the one type bragg reflector layers with those of the ideal FBAR with top and bottom electrode contacting air by using equivalent circuit technique. It is assumed that ZnO is used for piezoelectric film, $SiO_2$ are used for membrane layer and low acoustic impedance layer, W are used for the high acoustic reflector layer and Al is used for the electrode. Each layer is considered to have a acoustic propagation loss. ABCD parameters are picked out and input impedance is calculated by converting 1-port equivalent circuit to simplified equivalent circuit that ABCD parameters are picked out possible. From the variation of resonance frequency due to the change of thickness of electrode layers, reflector layers and membrane layer it is confirmed that membrane layer and the reflector layer just under the electrode have the greatest effect on the variation of resonance frequency. From the variation of resonance properties, K and electrical Q with the number of layers, K is not much affected by the number of layers but electrical Q increases with the number of layers when the number of layers is less than seven. The electrical Q is saturated when the number of layers is large than six. The electrical Q is dependent of mechanical Q of reflector layers and membrane layer. Both ladder filter and SCF (Stacked Crystal Filters) show higher insertion loss and out-of-band rejection with the increase of the number of resonators. The insertion loss decreases with the increase of the number of reflector layers but the bandwidth is not much affected by the number of reflector layers. Ladder Filter and SCF with membrane layer show the spurious response due to spurious resonance properties. Ladder filter shows better skirt-selectivity characteristics in bandwidth but SCF shows better characteristics in insertion loss.

• Korean Journal of Food Science and Technology
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• v.49 no.3
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• pp.274-278
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• 2017

In this study, predictive mathematical models were developed to estimate the kinetics of Staphylococcus aureus growth in processed meat product galbitang. Processed meat product galbitang was inoculated with 0.1 mL of S. aureus culture and stored at 4, 10, 20, $37^{\circ}C$. The ${\mu}_{max}$ (maximum specific growth rate) and LPD (lag phase duration) values were calculated. The primary model was used to develop a response surface secondary model. The growth parameters were analyzed using the square root model as a function of storage temperature. The developed model was confirmed by calculating RMSE (Root Mean Square Error) values as statistic parameters. The LPD decreased, but ${\mu}_{max}$ increased with an increase in the storage temperature. At 4, 10, 20 and $37^{\circ}C$, $R^2$ was 0.99, 0.98, 0.99 and 0.99, respectively; RMSE was 0.39. The developed predictive growth model can be used to predict the risk of S. aureus contamination in processed meat product galbitang; hence, it has potential as an input model for the risk assessment.