• Journal of the Society of Naval Architects of Korea
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• v.47 no.5
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• pp.709-718
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• 2010

This paper deals with two contents: first, distributions of plate slenderness ratios, stiffened plate slenderness ratios, and stiffener slenderness ratios, which include dimensions and material variables of stiffened plates, of stiffened plates of large-sized in-service vessels, and, second, comparison of compressive strengths. The investigated vessels consist of 59 tankers, 49 bulkers, 28 product carriers, 15 container carriers, and 12 multi-purpose vessels. The tankers are ranged from handymax class to VLCC and larger than Suezmax class. The sizes of the bulkers are 20K to 200K deadweight. The maximum size of containers is less than 5000TEU class. Two parameters for normal distributions of the slenderness ratios (mean and standard deviation) are suggested and probable ranges of the slenderness ratios are also graphically presented. The ultimate strengths of the stiffened plates are presented using the various simplified formulas and nonlinear FEAs. As well, average compressive strength curves, which are necessary for the estimation of the hull girder moment capacities, are proposed. It is proved that formulas for stiffened plates in CSR overestimate slightly in overall average strain range. Mode5 formula (plate buckling mode) in CSR show unreasonably conservative results with respect to the ultimate strengths rather than post-ultimate average compressive strengths.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.6
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• pp.170-176
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• 2018

Recently, weapon system requires personal protection products due to the explosion of rapid-fire explosion, which is considered to be multi threat in modernization, complication and war against terrorism. However, the conventional Korean military bullet protection helmets are not suitable for wearing convenience and combatant interoperability in terms of ergonomic. In this paper, we propose a suitable 3D Scanning method for the head, and compare the measured 3D dimension with the existing 2D measurement value to identity the reliability. Reverse engineered soldier head using the quick surface method was realized with a perfect free-form surface and satisfactory tolerance range (${\pm}0.2mm$). Through the comparison of 3D and 2D measured head dimensions, the absolute error value was 0.73 mm on average and relative error was 0.35 %, confirming the high accuracy of the 3D scan modeling. Also, quick surface method using 3D scanner is suggested a fast and accurate skill for ergonomics in obtaining the head modeling needed for military's personal bullet protection helmet design.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.333-340
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• 2022

The COVID-19 has made everyone anxious and people need to keep their distance. It is necessary to conduct collective assessment and screening of college students' mental health in the opening season of every year. This study uses and trains a multi-layer perceptron neural network model for deep learning to identify facial emotions. After the training, real pictures and videos were input for face detection. After detecting the positions of faces in the samples, emotions were classified, and the predicted emotional results of the samples were sent back and displayed on the pictures. The results show that the accuracy is 93.2% in the test set and 95.57% in practice. The recognition rate of Anger is 95%, Disgust is 97%, Happiness is 96%, Fear is 96%, Sadness is 97%, Surprise is 95%, Neutral is 93%, such efficient emotion recognition can provide objective data support for capturing negative. Deep learning emotion recognition system can cooperate with traditional psychological activities to provide more dimensions of psychological indicators for health.

• Convergence Security Journal
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• v.23 no.1
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• pp.117-123
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• 2023

To detect advanced ransomware attacks with machine learning-based models, the classification model must train learning data with high-dimensional feature space. And in this case, a 'curse of dimension' phenomenon is likely to occur. Therefore, dimensionality reduction of features must be preceded in order to increase the accuracy of the learning model and improve the execution speed while avoiding the 'curse of dimension' phenomenon. In this paper, we conducted classification of ransomware by applying three machine learning models and two feature extraction techniques to two datasets with extremely different dimensions of feature space. As a result of the experiment, the feature dimensionality reduction techniques did not significantly affect the performance improvement in binary classification, and it was the same even when the dimension of featurespace was small in multi-class clasification. However, when the dataset had high-dimensional feature space, LDA(Linear Discriminant Analysis) showed quite excellent performance.

• Smart Structures and Systems
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• v.30 no.5
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• pp.479-500
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• 2022

In this study, a new type of isolation bearing is proposed by combining S-shaped steel plate dampers (SSDs) with a spherical steel bearing, and the seismic control effect of a five-span standard high-speed railway bridge is investigated. The advantages of the proposed S-shaped steel damping friction bearing (SSDFB) are that it cannot only lengthen the structural periods, dissipate the seismic energy, but also prevent bridge unseating due to the restraint effectiveness of SSDs in the large relative displacements between the girders and piers. This study first presents a detailed description and working principle of the SSDFB. Then, mechanical modeling of the SSDFB was derived to fundamentally define its cyclic behavior and obtain key mechanical parameters. The numerical model of the SSDFB's critical component SSD was verified by comparing it with the experimental results. After that, parameter studies of the dimensions and number of SSDs, the friction coefficient, and the gap length of the SSDFBs were conducted. Finally, the longitudinal seismic responses of the bridge with SSDFBs were compared with the bridge with spherical bearing and spherical bearing with strengthened shear keys. The results showed that the SSDFB can not only significantly mitigate the shear force responses and residual displacement in bridge substructures but also can effectively reduce girder displacement and prevent bridge unseating, at a cost of inelastic deformation of the SSDs, which is easy to replace. In conclusion, the SSDFB is expected to be a cost-effective option with both multi-stage energy dissipation and restraint capacity, making it particularly suitable for seismic isolation application to high-speed railway bridges.

• Advances in nano research
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• v.15 no.3
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• pp.215-224
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• 2023

Nonlinearity plays an important role in control systems and the application of design. For this reason, in addition to linear vibrations, nonlinear vibrations of the stepped nanobeam are also discussed in this manuscript. This study investigated the vibrations of stepped nanobeams according to Eringen's nonlocal elasticity theory. Eringen's nonlocal elasticity theory was used to capture the nanoscale effect. The nanoscale stepped Euler Bernoulli beam is considered. The equations of motion representing the motion of the beam are found by Hamilton's principle. The equations were subjected to nondimensionalization to make them independent of the dimensions and physical structure of the material. The equations of motion were found using the multi-time scale method, which is one of the approximate solution methods, perturbation methods. The first section of the series obtained from the perturbation solution represents a linear problem. The linear problem's natural frequencies are found for the simple-simple boundary condition. The second-order part of the perturbation solution is the nonlinear terms and is used as corrections to the linear problem. The system's amplitude and phase modulation equations are found in the results part of the problem. Nonlinear frequency-amplitude, and external frequency-amplitude relationships are discussed. The location of the step, the radius ratios of the steps, and the changes of the small-scale parameter of the theory were investigated and their effects on nonlinear vibrations under simple-simple boundary conditions were observed by making comparisons. The results are presented via tables and graphs. The current beam model can assist in designing and fabricating integrated such as nano-sensors and nano-actuators.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.91-98
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• 2023

This study is an exploratory research on smart healthcare services, specifically focusing on a multi-channel CCR based healthcare service system. The study examines the overview and operational principles of the service system, highlighting the significance of user communication and its role in the system's functionality. Furthermore, the study investigates the impact of service quality on user satisfaction and intention to continue using the service. To achieve this, a structural equation modeling(SEM) analysis was conducted with a sample of 188 users who owned and utilized healthcare devices and apps. The results indicate that service quality dimensions (reliability, responsiveness, empathy, assurance, and tangibility) all had a positive influence on user satisfaction. Additionally, user satisfaction was found to have a significant impact on intention to continue using the service. The findings of this study contribute to exploring the effectiveness and potential value of CCR-based smart healthcare services. It was also provided insights for the future development of smart healthcare systems that offer accurate health information and personalized services for individual health management and prevention.

• Steel and Composite Structures
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• v.51 no.4
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• pp.441-456
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• 2024

This paper aims to develop Machine Learning (ML) algorithms to predict the buckling resistance of cold-formed steel (CFS) channels with restrained flanges, widely used in typical CFS sheathed wall panels, and provide practical design tools for engineers. The effects of cross-sectional restraints were first evaluated on the elastic buckling behaviour of CFS channels subjected to pure axial compressive load or bending moment. Feedforward multi-layer Artificial Neural Networks (ANNs) were then trained on different datasets comprising CFS channels with various dimensions and properties, plate thicknesses, and restraining conditions on one or two flanges, while the elastic distortional buckling resistance of the elements were determined according to the Finite Strip Method (FSM). To develop less biased networks and ensure that every observation from the original dataset has the chance of appearing in the training and test set, a K-fold cross-validation technique was implemented. In addition, the hyperparameters of the ANNs were tuned using a grid search technique to provide ANNs with optimum performances. The results demonstrated that the trained ANNs were able to predict the elastic distortional buckling resistance of CFS flange-restrained elements with an average accuracy of 99% in terms of coefficient of determination. The developed models were then used to propose a simple ANN-based design formula for the prediction of the elastic distortional buckling stress of CFS flange-restrained elements. Finally, the proposed formula was further evaluated on a separate set of unseen data to ensure its accuracy for practical applications.

• Journal of the Korea Institute of Building Construction
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• v.12 no.1
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• pp.122-132
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• 2012

Establishing a success model of a specific information system is critical to understanding the mechanism of IS success, the various dimensions of IS performance, and the factors and their causal relations in IS success. As one of the key IT applications, the project management information system (PMIS), particularly the web-based PMIS (Web-PMIS), has played a significant role in construction management processes in Korea. However, there have been few research attempts made to construct a Web-PMIS success model. This study primarily aims to propose a Web-PMIS success model based on DeLone and McLean's IS success model, and to discuss whether or not the D&M IS success model can be applied to the construction Web-PMIS. A questionnaire was sent out to Web-PMIS users (construction managers and constructors), and 253 completed questionnaires were received. Through multi-regression analysis, it was confirmed that it is statistically acceptable to apply the D&M IS success model to the Web-PMIS. However, the explanatory power of the model is not sufficient, and some of the model factors are not statistically significant enough. Relying on the statistical analysis results, this study also discusses the development direction for the Web-PMIS success model.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.3
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• pp.277-284
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• 2012

In this study, a heat-transfer performance analysis is carried out for a multi-channel volumetric air receiver for a solar power tower. On the basis of a series of reviews regarding the relevant literature, a calculation process is proposed for the prediction of the wall- and air- temperature distributions of a single channel at given geometric and input conditions. Furthermore, a unique mathematical model of the receiver effectiveness is presented through analysis of the temperature profile. The receiver is made of silicon carbide. A total of 225 square straight channels per module are molded to induce the air flow, and each channel has the dimensions of $2mm(W){\times}2mm(H){\times}0.2mm(t){\times}320mm(L)$. The heat-transfer rate, temperature distribution and effectiveness are presented according to the variation of the channel and module number under uniform irradiation and mass flow rate. The available air outlet temperature applied to the solar power tower should be over $700^{\circ}C$. This numerical model was actually used in the design of a 200 kW-level commercial solar air receiver, and the required number of modules satisfying the thermal performance could be obtained for the specified geometric and input conditions.