• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.489-498
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• 2023

Advancements in hardware performance and computing technology have facilitated the progress of climate prediction models to address climate change. The Korea Meteorological Administration employs the GloSea6 model with supercomputer technology for operational use. Various universities and research institutions utilize the Low-GloSea6 model, a low-resolution coupled model, on small to medium-scale servers for weather research. This paper presents an analysis using Intel VTune Profiler on Low-GloSea6 to facilitate smooth weather research on small to medium-scale servers. The tri_sor_dp_dp function of the atmospheric model, taking 1125.987 seconds of CPU time, is identified as a hotspot. Nonlinear regression models, a machine learning technique, are applied and compared to existing functions conducting numerical operations. The K-Nearest Neighbors regression model exhibits superior performance with MAE of 1.3637e-08 and SMAPE of 123.2707%. Additionally, the Light Gradient Boosting Machine regression model demonstrates the best performance with an RMSE of 2.8453e-08. Therefore, it is confirmed that applying a nonlinear regression model to the tri_sor_dp_dp function during the execution of Low-GloSea6 could be a viable alternative.

• Advances in nano research
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• v.16 no.4
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• pp.325-340
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• 2024

There are several novel uses for dispersing many nanoparticles into a conventional fluid, including dynamic sealing, damping, heat dissipation, microfluidics, and more. Therefore, melting heat and mass transfer characteristics of a 3-D MHD Hybrid Nanofluid flow over a rotating disc with presenting dufour and soret effects are assessed numerically in this study. In this instance, we investigated both ferric sulfate and molybdenum disulfide as nanoparticles suspended within base fluid water. The governing partial differential equations are transformed into linked higher-order non-linear ordinary differential equations by the local similarity transformation. The collection of these deduced equations is then resolved using a Chebyshev spectral collocation-based algorithm built into the Mathematica software. To demonstrate how different instances of hybrid/ nanofluid are impacted by changes in temperature, velocity, and the distribution of nanoparticle concentration, examples of graphical and numerical data are given. For many values of the material parameters, the computational findings are shown. Simulations conducted for different physical parameters in the model show that adding hybrid nanoparticle to the fluid mixture increases heat transfer in comparison to simple nanofluids. It has been identified that hybrid nanoparticles, as opposed to single-type nanoparticles, need to be taken into consideration to create an effective thermal system. Furthermore, porosity lowers the velocities of simple and hybrid nanofluids in both cases. Additionally, results show that the drag force from skin friction causes the nanoparticle fluid to travel more slowly than the hybrid nanoparticle fluid. The findings also demonstrate that suction factors like magnetic and porosity parameters, as well as nanoparticles, raise the skin friction coefficient. Furthermore, It indicates that the outcomes from different flow scenarios correlate and are in strong agreement with the findings from the published literature. Bar chart depictions are altered by changes in flow rates. Moreover, the results confirm doctors' views to prescribe hybrid nanoparticle and particle nanoparticle contents for achalasia patients and also those who suffer from esophageal stricture and tumors. The results of this study can also be applied to the energy generated by the melting disc surface, which has a variety of industrial uses. These include, but are not limited to, the preparation of semiconductor materials, the solidification of magma, the melting of permafrost, and the refreezing of frozen land.

• Journal of the Korean Geotechnical Society
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• v.40 no.3
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• pp.77-84
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• 2024

Aging and damaged underground utilities cause cavity and ground subsidence under roads, which can cause economic losses and risk user safety. This study used infrared cameras to assess the thermal characteristics of such cavities and evaluate their reliability using a CNN algorithm. PVC pipes were embedded at various depths in a test site measuring 400 cm × 50 cm × 40 cm. Concrete blocks were used to simulate road surfaces, and measurements were taken from 4 PM to noon the following day. The initial temperatures measured by the infrared camera were 43.7℃, 43.8℃, and 41.9℃, reflecting atmospheric temperature changes during the measurement period. The RP algorithm generates images in four resolutions, i.e., 10,000 × 10,000, 2,000 × 2,000, 1,000 × 1,000, and 100 × 100 pixels. The accuracy of the CNN model using RP images as input was 99%, 97%, 98%, and 96%, respectively. These results represent a considerable improvement over the 73% accuracy obtained using time-series images, with an improvement greater than 20% when using the RP algorithm-based inputs.

• The Korean Journal of Applied Statistics
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• v.37 no.1
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• pp.73-86
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• 2024

A radial chart of Excel is very useful graphical method in delivering information for numerical data. However, it is not easy to discriminate or classify many individuals. In this case, after shaping each individual of a radial chart, we need to apply shape analysis. For a radial chart, since landmarks for shaping are formed as many as the number of variables representing the characteristics of the object, we consider a shape that connects them to a line. If the shape becomes complicated due to the large number of variables, it is difficult to easily grasp even if visualized using a radial chart. Principal component analysis (PCA) is performed on variables to create a visually effective shape. The classification table and classification rate are checked by applying the techniques of traditional discriminant analysis, support vector machine (SVM), and artificial neural network (ANN), before and after principal component analysis. In addition, the difference in discrimination between the two coordinates of generalized procrustes analysis (GPA) coordinates and Bookstein coordinates is compared. Bookstein coordinates are obtained by converting the position, rotation, and scale of the shape around the base landmarks, and show higher rate than GPA coordinates for the classification rate.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.1
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• pp.9-16
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• 2024

Using the proper orthogonal decomposition (POD) based intrusive reduced order model (ROM), the total degrees of freedom of the structural system can be significantly reduced and the critical time step satisfying the conditional stability increases in the explicit time integrations. In this study, therefore, the changes in the critical time step in the explicit time integrations are investigated using both the POD-ROM and Voronoi-cell lattice model (VCLM). The snapshot matrix is composed of the data from the structural response under the arbitrary dynamic loads such as seismic excitation, from which the POD-ROM is constructed and the predictive capability is validated. The simulated results show that the significant reduction in the computational time can be achieved using the POD-ROM with sufficiently ensuring the numerical accuracy in the seismic analyses. In addition, the validations show that the POD based intrusive ROM is compatible with the Voronoi-cell lattice based explicit dynamic analyses. In the future study, the research results will be utilized as an elemental technology for the developments of the real-time predictive models or monitoring system involving the high-fidelity simulations of structural dynamics.

• Journal of IKEEE
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• v.28 no.2
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• pp.221-227
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• 2024

This paper presents a smartphone-attachable vascular compliance monitoring module. The proposed sensor module measures photoplethysmogram (PPG) and reconstructs an accelerated PPG waveform. The feature points are extracted from the accelerated PPG waves, and vascular compliance is estimated using these extracted features. The module is powered via the smartphone's USB terminal and transmits the acquired waveforms along with vascular compliance values through Bluetooth. The transmitted waveforms and vascular compliance value are displayed through the smartphone application. This work proposes an assessment method for consistency of PPG instrumentation, and it was implemented in a processor of sensor module. The proposed sensor module can be easily attached to smartphone that does not support PPG instrumentation, providing simple measurment and numerical analysis of vascular compliance. To verify the performance of the implemented sensor module, we acquired vascular compliance and pulse pressure data from 29 subjects. Pulse pressure, which serves as a representative indicator of vascular compliance, was obtained using a commercial blood pressure monitor. The analysis results showed that the Pearson coefficient between vascular compliance and pulse pressure was 0.778, confirming a relatively high correlation between two metrics.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.163-171
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• 2024

Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.347-357
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• 2024

Numerous prior studies have delineated the size distribution of noncohesive sediment in suspension, focusing on mean size and standard deviation. However, suspensions comprise a heterogeneous mixture of sediment particles of varying sizes. The transport dynamics of suspended sediment in turbulent flow are intimately tied to settling velocities calculated based on size and density. Consequently, understanding the grain size distribution becomes paramount in comprehending sediment transport phenomena for noncohesive sediment. This study aims to introduce a straightforward modeling approach for simulating the grain size distribution of suspended sediment amidst turbulence. Leveraging insights into the contrast between cohesive and noncohesive sediment, we have meticulously revised a stochastic flocculation model originally designed for cohesive sediment to aptly simulate the grain size distribution of noncohesive sediment in suspension. The efficacy of our approach is corroborated through a meticulous comparison between experimental data and the grain size distribution simulated by our newly proposed model. Through numerical simulations, we unveil that the modulation of grain size distribution of suspended sediment is contingent upon the sediment transport capacity of the carrier fluid. Hence, we deduce that our simplified approach to simulating the grain size distribution of suspended sediment, integrated with a sediment transport model, serves as a robust framework for elucidating the pivotal bulk properties of sediment transport.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.9-14
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• 2024

Hue, value, and chroma are the fundamental colour components used in colour property research to identify colour in the digital media environment. In the Munsell colour system, which is based on the characteristics of visual perception, the basic properties are classified into hue, value, and chroma. The methods for recording these three properties can be divided into the colour appearance system and the colour mixing system: in the former, they are documented based on a colour chart that focuses on visual perception, and in the latter, accurate numerical records are kept without concern for discolouration. Colour terminology is crucial for conveying and expressing colours, and colours can be classified and defined according to the combination of hue, value, and chroma. With the development of various media, it has become possible to represent a range of colours previously unachievable, necessitating basic research into the characteristics of colour perception by further subdividing digital-oriented colour studies. In this study, we conducted psychophysical experiments to identify and analyse the categories of value and chroma needed to recognise each colour among the ten representative colours of the Munsell colour system, based on visual perception on a display. This study analyses the results of these experiments, defines their significance as foundational research data on colour perception characteristics, and suggests directions for future research.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.4
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• pp.348-357
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• 2024

Maneuvering performance is crucial for fishing vessels, especially under operational conditions that involve frequent course changes and weight variations due to catch. Small vessel accidents account for approximately 60% of maritime incidents as of 2022, mainly attributed to collisions and stranding accidents due to insufficient maneuvering performance. Especially, accidents that occur on small vessels less than 10 tons account for about 65% of all accidents. The absence of international standards presents challenges in accurately evaluating the maneuvering performance of small vessels. In this study, a 4.99-ton small fishing vessel was selected as the target, and a 3d-cad model was created. The commercial numerical analysis program STAR-CCM+ was employed to establish a simulation environment for the vessel's maneuvring motion. Based on this standard loading conditions and weight distribution were considered, 10° / 10°, 20° / 20° zigzag tests and 35° turning test were conducted. The results revealed a tendency for decreased yaw and course-keeping performance and improved turning performance as the hull weight increased. However, in partial arrival and full load departure condition, the manoeuvering performance were relatively poor. Based on this, the need for evaluation of maneuvering and standardized criteria of maneuvering performance for safe navigation of small vessels is presented. Furthermore, it is expected that the evaluation results of maneuvering performance in this study can serve as fundamental data for establishing criteria for evaluating the maneuvering performance of small vessels.