• Journal of the Korean institute of surface engineering
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• v.54 no.5
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• pp.230-237
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• 2021

In this study, the influence of silicon contents on the microstructure, mechanical and tribological properties of Ti-Al-Si-N coatings were systematically investigated for application of cutting tools. The composition of the Ti-Al-Si-N coatings were controlled by different combinations of TiAl₂ and Ti₄Si composite target powers using an arc ion plating technique in a reactive gas mixture of high purity Ar and N₂ during depositions. Ti-Al-Si-N films were nanocomposite consisting of nanosized (Ti,Al,Si)N crystallites embedded in an amorphous Si₃N₄/SiO₂ matrix. The instrumental analyses revealed that the synthesized Ti-Al-Si-N film with Si content of 5.63 at.% was a nanocomposites consisting of nano-sized crystallites (5-7 nm in dia.) and a three dimensional thin layer of amorphous Si₃N₄ phase. The hardness of the Ti-Al-Si-N coatings also exhibited the maximum hardness value of about 47 GPa at a silicon content of ~5.63 at.% due to the microstructural change to a nanocomposite as well as the solid-solution hardening. The coating has a low friction coefficient of 0.55 at room temperature against an Inconel alloy ball. These excellent mechanical and tribological properties of the Ti-Al-Si-N coatings could help to improve the performance of machining and cutting tool applications.

• 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.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.1
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• pp.125-137
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• 2019

This study determined the impact of 'Fashion Augmented Reality (FAR)' acceptance factors based on the model of acceptance and use of technology (UTAUT) on consumer attitudes, intention to use technology, and fashion product purchase intention. A survey asked participants to have an AR experience using a FAR app to understand FAR in advance. Data were analyzed factor analysis and stepwise regression using SPSS. The results are as follows. First, the factor analysis classified the acceptance variables of FAR technology into 'social relations', 'shopping effectiveness', and 'easy to use FAR'. Second, among the three factors of FAR acceptance, 'shopping effectiveness' is statistically more influential on positive attitudes towards FAR. However, 'easy to use' factor was more influential on 'the intention to use technology' as well as 'purchase intention'. Third, 'social relations' were identified as an important factor affecting 'consumer attitudes', 'intention to use technology' and 'purchase intention' which are not well covered in fashion technology research. In addition, 'the intention to use technology' was found to be influential on 'purchase intention' and indicated the importance of easiness of FAR to enhance purchase intention.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.341-350
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• 2022

In this paper, we propose a deep learning based on-device augmented reality (AR) system in which multiple input images are used to implement the correct occlusion in a real environment. The proposed system is composed of three technical steps; camera pose estimation, depth estimation, and object augmentation. Each step employs various mobile frameworks to optimize the processing on the on-device environment. Firstly, in the camera pose estimation stage, the massive computation involved in feature extraction is parallelized using OpenCL which is the GPU parallelization framework. Next, in depth estimation, monocular and multiple image-based depth image inference is accelerated using the mobile deep learning framework, i.e. TensorFlow Lite. Finally, object augmentation and occlusion handling are performed on the OpenGL ES mobile graphics framework. The proposed augmented reality system is implemented as an application in the Android environment. We evaluate the performance of the proposed system in terms of augmentation accuracy and the processing time in the mobile as well as PC environments.

• Journal of The Korean Association of Information Education
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• v.26 no.3
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• pp.219-227
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• 2022

Students are always preparing for remote classes while taking face-to-face classes due to COVID-19. However, it is true that the class satisfaction with distance learning is not high for students and teachers. The idea that even if remote classes are conducted at home, it would be nice to have classes together like real ones, the need for a virtual world education program that utilizes augmented reality and virtual reality based on the metaverse has emerged. However, there are very few studies that teachers try to apply them to their classes. In this study, a metaverse application curriculum was presented for elementary science and 'space' domains. To implement the metaverse, ZEPETO and COSPACIS EDU were used. In the analysis of content creation with students and evaluation with schoolmates, this study showed that the concentration of learning was increased and creativity improved in the 'real', 'individual', and 'society' domains.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.425-437
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• 2022

In this study, the role and function of Edutech, as well as the application and expectations in the field of future vocational competency development, were gathered to define Edutech as a comprehensive working definition. Based on this redefinition of Edutech, this study analyzes Edutech technology trends and examines the level of actual technology applied to education and vocational training based on written interviews with experts, and finds out significant implications from the point of view of vocational training. Finally we propose an Edutech-based Vocational Education and Training Model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.1-8
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• 2022

Recently, Google MedeiaPipe presents a novel approach for neural network-based hair segmentation from a single camera input specifically designed for real-time, mobile application. Though neural network related to hair segmentation is relatively small size, it produces a high-quality hair segmentation mask that is well suited for AR effects such as a realistic hair recoloring. However, it has undesirable segmentation effects according to hair styles or in case of containing noises and holes. In this study, the energy function of the test image is constructed according to the estimated prior distributions of hair location and hair color likelihood function. It is further optimized according to graph cuts algorithm and initial hair region is obtained. Finally, clustering algorithm and image post-processing techniques are applied to the initial hair region so that the final hair region can be segmented precisely. The proposed method is applied to MediaPipe hair segmentation pipeline.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.9-15
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• 2023

Metaverse is a modern new technology that is advancing quickly. The goal of this study is to investigate this technique from the perspective of computer vision as well as general perspective. A thorough analysis of computer vision related Metaverse topics has been done in this study. Its history, method, architecture, benefits, and drawbacks are all covered. The Metaverse's future and the steps that must be taken to adapt to this technology are described. The concepts of Mixed Reality (MR), Augmented Reality (AR), Extended Reality (XR) and Virtual Reality (VR) are briefly discussed. The role of computer vision and its application, advantages and disadvantages and the future research areas are discussed.

• Transactions of the Korean hydrogen and new energy society
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• v.10 no.1
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• pp.59-69
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• 1999

AlN thin films were fabricated by reactive sputtering for the application of MIS devices with Al/AlN/Si structure. It has investigated the surface morphology change, I-V characteristics, C-V characteristics, and chemical composition of AlN films with the intriducing time of hydrogen on the fixed deposition condition(RF power: 150W, sputtering pressure: 5mTorr, flow rate ratio of $Ar/N_2=1$, hydrogen concentration: 5%). By addition of the hydrogen the deposition rate decreased drastically whereas the surface morphology changed little. It has been found from the analysis of I-V and C-V characteristics curves that the films deposited with hydrogen addition in initial stage had lower leakage current density, lower flat band voltage and hystersis profile when compared with those with hydrogen addition in last stage. The oxygen concentration in AlN films decreased with addition of hydrogen gas, which suggesting a profitable role in the insulation and C-V characteristics of AlN films.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.971-978
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• 2022

As a marketing method in a non-face-to-face society, the purpose of this study is to test how AR experience affects purchase intention in the process of consumers recognizing product information to purchase products and to secure the basis for the effectiveness of developing and introducing augmented reality functions in future product brand applications. Literary research methods and empirical research methods were used to verify the research purpose, and to measure this, an application of domestic tableware brand 'Odense', which implements augmented reality functions, was produced and used as an experimental tool. Also, a direct causal relationship was attempted by constituting a questionnaire by deriving a measurement scale for perceived usefulness, perceived ease, perceived pleasure, and purchase, which are factors of technology acceptance theory (TAM), and empirical analysis was conducted using the SPSS 25.0 statistical package to achieve the purpose of the study. As a result of the study, significant results were derived from all factors in the effect of perceived usefulness, ease, and pleasure on purchase intention, and several significant differences were found among factors according to gender, age, and internet shopping usage time in general characteristics. In conclusion, the user experience of the medium in which the augmented reality function is introduced in the information recognition stage of the product has a positive effect on purchase compared to the user experience of existing applications.