• Journal of Fashion Business
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• v.1 no.2
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• pp.1-19
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• 1997

This thesis is a reflection of Korean aestheticism and how it has evolved and influenced Korean contemporary fashion throughout the last century. Up to the current, there have been five notable trends of fashion that have been influenced from and have reflected the qualities emblematic of various periods in Korean history. They can be characterized as the era of Missionary fashion, Uniform fashion, Salon fashion, Brand Name Fashion, and finally, fashion from the current era of diversification. The specific characteristics of each fashion era have been analized and illustrated in a comprehensive table. Design characteristics of Korean contemporary fashion are as follows : 1. A point of emphasis is given to facial feature, unconstructive design and ample silhouette and A silhouette, two-piece and pants. Korean style wrap skirt, a smooth curve and layered style. 2. Effect of flatness from material; as methods of quilting, reinforced dual stitching(Kaeki), patchwork, embroidery and goldfoil thread extra, it is turned up that texture of cloth stuff and effects of flatness. 3. Simple color combinations give effects in two different directions For instance, white and a variety of vivid colors, a dull color and bright colors, black, blue. 4. Over-design, diffusion of fashion. Based on the design characteristics described above, the essence of Korea's beauty consciousness can be captured and summarized through the following points: 1. Emotionalism and non-characterism: traditional and simple natural beauty and modernized natural beauty. 2. From authoritism to non-authoritism: traditional and formal personal beauty and casual characteristic beauty. 3. Polaris (antithesis) phenomenon: chastic beauty and ostentatious beauty, simplicity and lavishness, conformity of fashion and originality. Although the beauty consciousness of Korean contemporary fashion is changing from traditional passive metaphor to aesthetic expressionism for the new generation, after all the basic foundation or root of the spiritual beauty of idealism is usually recognized by focusing on the face.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.61-74
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• 2012

In this paper, we propose a illumination-robust face recognition system using MCS-LBP and 2D-PCA algorithm. A binary pattern transform which has been used in the field of the face recognition and facial expression, has a characteristic of robust to illumination. Thus, this paper propose MCS-LBP which is more robust to illumination than previous LBP, and face recognition system fusing 2D-PCA algorithm. The performance evaluation of proposed system was performed by using various binary pattern images and well-known face recognition features such as PCA, LDA, 2D-PCA and ULBP histogram of gabor images. In the process of performance evaluation, we used a YaleB face database, an extended YaleB face database, and a CMU-PIE face database that are constructed under varying lighting condition, and the proposed system which consists of MCS-LBP image and 2D-PCA feature show the best recognition accuracy.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.7 no.1
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• pp.49-52
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• 1977

The authors had observed a case of cleidocranial dysostosis of 42 years old unmarried woman. The observation was founded upon roentgenogram of skull P-A view, orthopantomograph, cephalometric view, chest P-A view and wrist X-ray view. The patient gave a dwarfic impression with 145㎝ body height and concaved mandibular prognastic facial feature. The palate was narrowed and extremely high arched. The eruption state of teeth were extremely poor, only four teeth were erupted, composed of upper third molar and lower three deformed teeth. The skull P-A view of roentgenogram reveals overlying metopic suture, extends from the nasion to the sagittal suture, and the suture are delayed up to date and many wormian bones are formed. On the cephalometric view the maxilla is underdeveloped and produce the false mandibular prognathism. Twenty four impacted teeth can be detected by orthopantmograph, twelve in upper jaw and twelve in lower jaw. There are many supernumerary teeth, one in upper jaw and seven in lower jaw. On the chest P-A view, the clavicles are totally aplastic, but a vestige of clavicle is visible in the right side. On the wrist roentgenogram, the epiphyseal ossification of distal phalanx, mesial phalanx and proximal phalanx is delayed.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.205-208
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• 2013

Generally, binary pattern transforms have been used in the field of the face recognition and facial expression, since they are robust to illumination. Thus, this paper proposes an illumination-robust face recognition system combining an MLDP, which improves the texture component of the LDP, and a 2D-PCA algorithm. Unlike that binary pattern transforms such as LBP and LDP were used to extract histogram features, the proposed method directly uses the MLDP image for feature extraction by 2D-PCA. The performance evaluation of proposed method was carried out using various algorithms such as PCA, 2D-PCA and Gabor wavelets-based LBP on Yale B and CMU-PIE databases which were constructed under varying lighting condition. From the experimental results, we confirmed that the proposed method showed the best recognition accuracy.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.167-174
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• 2013

TIn this paper, we find the face in color images and the ability to track the face was implemented. Face tracking is the work to find face regions in the image using the functions of the computer system and this function is a necessary for the robot. But such as extracting skin color in the image face tracking can not be performed. Because face in image varies according to the condition such as light conditions, facial expressions condition. In this paper, we use the skin color pixel extraction function added lighting compensation function and the entire processing system was implemented, include performing finding the features of eyes, nose, mouth are confirmed as face. Lighting compensation function is a adjusted sine function and although the result is not suitable for human vision, the function showed about 4% improvement. Face features are detected by amplifying, reducing the value and make a comparison between the represented image. The eye and nose position, lips are detected. Face tracking efficiency was good.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.288-296
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• 2021

Automated face recognition in a runtime environment is gaining more and more important in the fields of surveillance and urban security. This is a difficult task keeping in mind the constantly volatile image landscape with varying features and attributes. For a system to be beneficial in industrial settings, it is pertinent that its efficiency isn't compromised when running on roads, intersections, and busy streets. However, recognition in such uncontrolled circumstances is a major problem in real-life applications. In this paper, the main problem of face recognition in which full face is not visible (Occlusion). This is a common occurrence as any person can change his features by wearing a scarf, sunglass or by merely growing a mustache or beard. Such types of discrepancies in facial appearance are frequently stumbled upon in an uncontrolled circumstance and possibly will be a reason to the security systems which are based upon face recognition. These types of variations are very common in a real-life environment. It has been analyzed that it has been studied less in literature but now researchers have a major focus on this type of variation. Existing state-of-the-art techniques suffer from several limitations. Most significant amongst them are low level of usability and poor response time in case of any calamity. In this paper, an improved face recognition system is developed to solve the problem of occlusion known as FRS-OCC. To build the FRS-OCC system, the color and texture features are used and then an incremental learning algorithm (Learn++) to select more informative features. Afterward, the trained stack-based autoencoder (SAE) deep learning algorithm is used to recognize a human face. Overall, the FRS-OCC system is used to introduce such algorithms which enhance the response time to guarantee a benchmark quality of service in any situation. To test and evaluate the performance of the proposed FRS-OCC system, the AR face dataset is utilized. On average, the FRS-OCC system is outperformed and achieved SE of 98.82%, SP of 98.49%, AC of 98.76% and AUC of 0.9995 compared to other state-of-the-art methods. The obtained results indicate that the FRS-OCC system can be used in any surveillance application.

• The Research Journal of the Costume Culture
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• v.32 no.3
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• pp.398-418
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• 2024

This study aims to examine how the body and clothing of Jesus Christ are represented in the Russian Transfiguration of Christ icons of the 15th and 16th centuries and why it is considered to have established a distinct Russian iconography free from Byzantine influence. The study analyzes the Russian icons comparing them with their Byzantine prototypes to identify the distinctive 'Russianness' of the representation. The research methods comprise a qualitative analysis of the literature on Russian Orthodoxy, Russian icons, Christian theology, and Christ's clothing and an empirical analysis of the icons. The scope of the study is limited to Russian icons from the 15th and 16th centuries and Byzantine icons from the 9th century onwards. The study found that, compared to Byzantine icons, the Russian icons exhibit a more elongated body, darker facial features, and lighter clothing. A statistical analysis using the Mann-Whitney U test further revealed that the Russian icons feature a stiffer, simpler form, more opaque material, and more defined clothing boundaries. These stylistic differences suggest that the 'Russianness' in the expression of Christ's body and clothing in the Transfiguration of Christ icons derives from creativity, abstractness, and tradition. Rather than a simple recreation of the historical Christ or adherence to the Byzantine tradition, the Russian iconographic representation emphasizes Christ's transfiguration into a luminous form, as described in the Bible, accentuating his divine nature over his human aspects.

• Anatomy and Cell Biology
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• v.57 no.1
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• pp.25-30
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• 2024

The aim of this study was to identify the anatomical feature of retaining ligament and fat compartment on the lower eyelid and infraorbital region using a histological method, and to investigate clear definitions for them which could be used generally in the clinical area. Eighteen specimens from eight fresh Korean cadavers were stained with Masson trichrome or hematoxylin and eosin. The ligamentous and fascial fibrous tissue were clearly identified. The ligamentous fibrous tissue which traversed in the superficial and deep fat layer was skin ligament and orbicularis retaining ligament (ORL). The fascial fibrous tissue enclosed the orbicularis oculi muscle (OOc) and circumferencial adipose tissue. Based on the ligamentous and fascial structure, three fat compartments, septal, suborbicularis oculi and infraorbital fat compartment, could be identified. The OOc attached to orbital rim and dermis by ORL and skin ligament, and the muscle fascicle and fat fascicle provided the connection point to the ORL and skin ligament as enclosing all muscle and fat tissue. The combination of the force made by the skin ligament in the lower eyelid and ORL may decide the level and form of the infraorbital grooves.

• Journal of IKEEE
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• v.28 no.3
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• pp.390-396
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• 2024

Vision Transformer (ViT) learns relationships between patches, but it may overlook important features such as color, texture, and boundaries, which can result in performance limitations in fields like medical imaging or facial recognition. To address this issue, this study proposes the Pairwise Attention Reinforcement (PAR) model. The PAR model takes both the training image and a reference image as input into the encoder, calculates the similarity between the two images, and matches the attention score maps of images with high similarity, reinforcing the matching areas of the training image. This process emphasizes important features between images and allows even subtle differences to be distinguished. In experiments using clock-drawing test data, the PAR model achieved a Precision of 0.9516, Recall of 0.8883, F1-Score of 0.9166, and an Accuracy of 92.93%. The proposed model showed a 12% performance improvement compared to API-Net, which uses the pairwise attention approach, and demonstrated a 2% performance improvement over the ViT model.

• The korean journal of orthodontics
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• v.26 no.2 s.55
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• pp.205-218
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• 1996

A given facial type can be considered as a syndrome in which various features are aggregated, so a single parameter is not sufficient to accurately identify a given facial type. This study was designed to identify & characterize the skeletal types that blend under the headline-'Cl III,deepbite'. Cephalograms of thirty-four untreated mixed dentition patients, selected mainly on the basis of clinical impression of Cl III with reduced lower face heights were studied. The following conclusion can be drawn. 1. Cl III malocclusion with reduced lower face height could be classified into three types. 2. Subtype 1 was identified by the following features : strong ramus, more anteriorly positioned upper molars without alveolar hypoplasia, acutely reduced Mn. plane angle. 3. Subtype 2 was characterized by a short ramus, sharply reduced postrior alveolar height, and normal Mn. plane angle. In general, this type had hypoplasia tendency in the vertical dimension. 4. In subtype 3, the AUFH occupying more percentage than ALFH was a outstanding feature. Ramal height was in normal range, alveolar hypoplasia and slightly reduced Mn. plane angle was observed. 5. The features of the subtypes were reflected in certain indices, which can be regarded as discriminative index. LAFH: if reduced, regardless of subtypes, indicates reduced lower ant. face height consistently. FHR: when this ratio is increased, it indicates subtype 1. FHI: when this ratio is in normal range, it indicates subtype 2. FPI: if reduced greatly, it indicates subtype 3.