• Korean Institute of Interior Design Journal
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• v.19 no.1
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• pp.180-189
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• 2010

Since collective houses are started to be supplied, the housing market has been transformed from supplier to demander oriented, and various type with same area of unit households have been deigned and started to be distributed. It can be expected that such transfer phenomenon would be continuously sped-up, and unit household will be more subdivided and varied. Thus, we analysed and studied the planes with subject of unit households in national housing scale ($85m^2$) that is treated as supply standard and has biggest volume in construction by Korean housing corporation. The analysing method is investigating the area of each room within unit household, calculating their minimum, maximum, and average values, studying the efficiency of unit household plane according to the structure of each room by comparative analysis these values, and analysing changing matter by investigating any change of each room area. The analysing results of which are followings. At first, number of BAY on face is increasing. Second, allocation of each room has been vary. Third, area ratio among bedroom1, livingroom, diningroom/kitchen become similar. Fourth, the area of diningroom/kitchen become somewhat bigger. Fifth, the space for passage way is efficiently allocated. Sixth, service area is reduced, Seventh, stereotyped phenomenon Is appeared. Based on many studies so far, any improvements of unit householder in national housing scale are followings. First, in terms of forming style, unit householder in national housing scale is unfolded in various way though, the form of each room is not more than typical style. Second, it shows stereotyped phenomenon. Especially, bathroom 1, 2 show stereotyped feature in terms of their type and area across entire research years, also LDK allocation method is stereotyped, as well as stereotyped trend in bedroom 2, 3, allocation for 4 BAY type.

• Archives of Plastic Surgery
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• v.38 no.4
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• pp.451-457
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• 2011

Purpose: As a central feature of the face, the nose has considerable significance in appearance and expression. Reconstruction of full thickness defects of the nasal ala has always been a challenge because of the 3-dimensional structure. For reconstruction of post burn defects of ala, skin graft, local or pedicled flap and composite graft are optionally available. We have reconstructed the ala defects using adiposocutaneous graft and observed the outcome. Methods: From March 2003 to December 2010, 19 cases in 11 patients with scar contracture and defect on ala portion were performed operation using adiposocutaneous graft. As a donor site, we used the inguinal crease and posterior auricular area and the donor site was primarily closed. We made incision through the superior rim of ala and released fully. A graft is applied to recipient site with larger size than recipient volume. Results: The mean age of the patient was 38.6 years (16~51), males are seven patients and females are four patients. The operation was performed bilaterally in 5 patients and unilaterally in 6 patients. Composite grafts were harvested from inguinal area in 13 cases and posterior auricular area in 6 cases. In one case, we did 4 times of operation to get enough volume. All the grafts were well taken. The mean size of the graft was 3.63 $cm^2$. Conclusion: For reconstruction of post burn defects of ala, it's not easy to use local flap or pedicled flap because of hardness and fibrosis of surrounding tissue. So, we choose adiposocutaneous graft for ala deformity reconstruction, got satisfactory outcome in color matching and texture.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.573-580
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• 2005

In this paper, we propose an emotion recognition using static and dynamic facial images to effectively design human interface. The proposed method is constructed by HMM(Hidden Markov Model), PCA(Principal Component) and wavelet transform. Facial database consists of six basic human emotions including happiness, sadness, anger, surprise, fear and dislike which have been known as common emotions regardless of nation and culture. Emotion recognition in the static images is performed by using the discrete wavelet. Here, the feature vectors are extracted by using PCA. Emotion recognition in the dynamic images is performed by using the wavelet transform and PCA. And then, those are modeled by the HMM. Finally, we obtained better performance result from merging the recognition results for the static images and dynamic images.

• Journal of the Korea Safety Management & Science
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• v.14 no.4
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• pp.229-238
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• 2012

Within last 10 years, internet has become a daily activity, and humankind had to face the Data Deluge, a dramatic increase of digital data (Economist 2012). Due to exponential increase in amount of digital data, large scale data has become a big issue and hence the term 'big data' appeared. There is no official agreement in quantitative and detailed definition of the 'big data', but the meaning is expanding to its value and efficacy. Big data not only has the standardized personal information (internal) like customer information, but also has complex data of external, atypical, social, and real time data. Big data's technology has the concept that covers wide range technology, including 'data achievement, save/manage, analysis, and application'. To define the connected technology of 'big data', there are Big Table, Cassandra, Hadoop, MapReduce, Hbase, and NoSQL, and for the sub-techniques, Text Mining, Opinion Mining, Social Network Analysis, Cluster Analysis are gaining attention. The three features that 'bid data' needs to have is about creating large amounts of individual elements (high-resolution) to variety of high-frequency data. Big data has three defining features of volume, variety, and velocity, which is called the '3V'. There is increase in complexity as the 4th feature, and as all 4features are satisfied, it becomes more suitable to a 'big data'. In this study, we have looked at various reasons why companies need to impose 'big data', ways of application, and advanced cases of domestic and foreign applications. To correspond effectively to 'big data' revolution, paradigm shift in areas of data production, distribution, and consumption is needed, and insight of unfolding and preparing future business by considering the unpredictable market of technology, industry environment, and flow of social demand is desperately needed.

• Coupled systems mechanics
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• v.7 no.6
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• pp.649-668
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• 2018

In this paper, we present a numerical model for fluid-structure interaction between structure built of porous media and acoustic fluid, which provides both pore pressure inside porous media and hydrodynamic pressures and hydrodynamic forces exerted on the upstream face of the structure in an unified manner and simplifies fluid-structure interaction problems. The first original feature of the proposed model concerns the structure built of saturated porous medium whose response is obtained with coupled discrete beam lattice model, which is based on Voronoi cell representation with cohesive links as linear elastic Timoshenko beam finite elements. The motion of the pore fluid is governed by Darcy's law, and the coupling between the solid phase and the pore fluid is introduced in the model through Biot's porous media theory. The pore pressure field is discretized with CST (Constant Strain Triangle) finite elements, which coincide with Delaunay triangles. By exploiting Hammer quadrature rule for numerical integration on CST elements, and duality property between Voronoi diagram and Delaunay triangulation, the numerical implementation of the coupling results with an additional pore pressure degree of freedom placed at each node of a Timoshenko beam finite element. The second original point of the model concerns the motion of the outside fluid which is modeled with mixed displacement/pressure based formulation. The chosen finite element representations of the structure response and the outside fluid motion ensures for the structure and fluid finite elements to be connected directly at the common nodes at the fluid-structure interface, because they share both the displacement and the pressure degrees of freedom. Numerical simulations presented in this paper show an excellent agreement between the numerically obtained results and the analytical solutions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.49-52
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• 2019

Braille guide block of sidewalk is an essential facility for independent walking of the blind. The blind walks while checking the braile guide blocks with white cane and sense of sole. When they leave the braile area, they face difficulties until they find the braile guide blocks again. In this paper, we propose an algorithm that guides the walking of the blind by determining whether they follows the braille guide blocks safely. For this purpose, the slope of the braille block is selected as a feature and a 3-line detector is introduced. Also the slopes are stabilized using spatial filtering to deal with breaks or junctions of the braille block during the progress and temporal filtering to cope with ego-motion of the blind. Through simulations using a dataset obtained from the real sidewalks and indoors, it can be shown that the proposed algorithm can successfully estimate the walking direction and determine whether the blind is out of the braille guide block area.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.173-182
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• 2009

In this paper, we studied about the extraction of the parameter and implementation of speechreading system to recognize the Korean 8 vowel. Face features are detected by amplifying, reducing the image value and making a comparison between the image value which is represented for various value in various color space. The eyes position, the nose position, the inner boundary of lip, the outer boundary of upper lip and the outer line of the tooth is found to the feature and using the analysis the area of inner lip, the hight and width of inner lip, the outer line length of the tooth rate about a inner mouth area and the distance between the nose and outer boundary of upper lip are used for the parameter. 2400 data are gathered and analyzed. Based on this analysis, the neural net is constructed and the recognition experiments are performed. In the experiment, 5 normal persons were sampled. The observational error between samples was corrected using normalization method. The experiment show very encouraging result about the usefulness of the parameter.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.290-293
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• 2021

In this paper, we implement a learning efficiency verification system to inspire learning motivation and help improve concentration by detecting the situation of the user studying. To this aim, data on learning attitude and concentration are measured by extracting the movement of the user's face or body through a real-time camera. The Jetson board was used to implement the real-time embedded system, and a convolutional neural network (CNN) was implemented for image recognition. After detecting the feature part of the object using a CNN, motion detection is performed. The captured image is shown in a GUI written in PYQT5, and data is collected by sending push messages when each of the actions is obstructed. In addition, each function can be executed on the main screen made with the GUI, and functions such as a statistical graph that calculates the collected data, To do list, and white noise are performed. Through learning efficiency checking system, various functions including data collection and analysis of targets were provided to users.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.93-101
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• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.

• Computers and Concrete
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• v.33 no.1
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• pp.27-39
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• 2024

In this study, the authors investigate the free vibration behavior of three-phases functionally graded sandwich plates using a novel nth-order shear deformation theory. These plates are composed of a homogeneous core and two face-sheet layers made of different functionally graded materials. This is the novel type of the sandwich structures that can be applied in many fields of mechanical engineering and industrial. The proposed theory only requires four unknown displacement functions, and the transverse displacement does not need to be separated into bending and shear parts, simplifying the theory. One noteworthy feature of the proposed theory is its ability to capture the parabolic distribution of transverse shear strains and stresses throughout the plate's thickness while ensuring zero values on the two free surfaces. By eliminating the need for shear correction factors, the theory further enhances computational efficiency. Equations of motion are established using Hamilton's principle and solved via Navier's solution. The accuracy and efficiency of the proposed theory are verified by comparing results with available solutions. The authors then use the proposed theory to investigate the free vibration characteristics of three-phases functionally graded sandwich plates, considering the effects of parameters such as aspect ratio, side-to-thickness ratio, skin-core-skin thicknesses, and power-law indexes. Through careful analysis of the free vibration behavior of three-phases functionally graded sandwich plates, the work highlighted the significant roles played by individual material ingredients in influencing their frequencies.