• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.7
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• pp.267-278
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• 2017

The aim of this paper was to develop a scale for measuring gender identity among sports participants (114 male, 193 female). Gender similarities and latent mean analysis was used to validate the gender identity measurement method. Data processing was carried out by way of frequency analysis, exploratory and confirmatory factor analysis, reliability, correlation, normal distribution of questions, and latent mean analysis using SPSS 18.0 and AMOS 18.0. The results of this study were as follows: First, the equivalence had revealed the configurable, metric, and scalar invariance of the scale that can be used in multi-groups in the same way. Second, women had a more open inclination than men when it came to participating in sports activities (p<.001). Third, women participating in sports activities tended to be more conservative than men (p<.001). Fourth, women who participated in sports activities showed a higher subjective tendency than men (p<.001). Fifth, there was no statistical difference in the outward tendency when participating in sports activities (p<.05). The results of this study suggest that gender identity among sports participants is not influenced by the changing times and the advancement of women in society.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.957-966
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• 2018

Recently, the demand for remote patient monitoring based on IoT has been increased due to aging population and an increase in single-person household. A non-contact biological signal measurement system using multiple IR-UWB radars for remote patient monitoring is proposed in this paper. To reduce error signals, a multilayer Subtraction algorithm is applied because when the background subtraction algorithm was applied to the biological signal processing, errors occurred such as voltage noise and staircase phenomenon. Therefore, a multilayer background subtraction algorithm is applied to reduce error occurrence. The multilayer background subtraction algorithm extracts the signal by calculating the amount of change between the previous clutter and the current clutter. In this study, the SVD algorithm is used. We applied the improved multilayer background subtraction algorithm to biological signal measurement and computed the respiration rate through Fast Fourier Transform (FFT). To verify the proposed system using IR-UWB radars and multilayer background subtraction algorithm, the respiration rate was measured. The validity of this study was verified by obtaining a precision of 97.36% as a result of a control experiment with Neulog's attachment type breathing apparatus. The implemented algorithm improves the inconvenience of the existing contact wearable method.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.383-391
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• 2017

In image processing, image segmentation has been studied by various methods in a long time. Image segmentation is the process of partitioning a digital image into multiple objects and face detection is a typical image segmentation field being used in a variety of applications that identifies human faces in digital images. In this paper, we propose a method for extracting the contours of faces included in images. Using the Viola-Jones algorithm, to do this, we detect the approximate locations of faces from images. But, the Viola-Jones algorithm could detected the approximate location of face not the correct position. In order to extract a more accurate face region from image, we use skin color in this paper. In details, face region would be extracted using the analysis of horizontal and vertical histograms on the skin area. Finally, the face contour is extracted using snake algorithm for the extracted face area. In this paperr, a modified snake energy function is proposed for face contour extraction based snake algorithm proposed by Williams et al.[7]

• Journal of the Microelectronics and Packaging Society
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• v.30 no.2
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• pp.65-70
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• 2023

Nanoimprint lithography (NIL) has attracted much attention due to its process simplicity, excellent patternability, process scalability, high productivity, and low processing cost for pattern formation. However, the pattern size that can be implemented on metal materials through conventional NIL technologies is generally limited to the micro level. Here, we introduce a novel hard imprint lithography method, extreme-pressure imprint lithography (EPIL), for the direct nano-to-microscale pattern formation on the surfaces of metal substrates with various thicknesses. The EPIL process allows reliable nanoscopic patterning on diverse surfaces, such as polymers, metals, and ceramics, without the use of ultraviolet (UV) light, laser, imprint resist, or electrical pulse. Micro/nano molds fabricated by laser micromachining and conventional photolithography are utilized for the nanopatterning of Al substrates through precise plastic deformation by applying high load or pressure at room temperature. We demonstrate micro/nanoscale pattern formation on the Al substrates with various thicknesses from 20 ㎛ to 100 mm. Moreover, we also show how to obtain controllable pattern structures on the surface of metallic materials via the versatile EPIL technique. We expect that this imprint lithography-based new approach will be applied to other emerging nanofabrication methods for various device applications with complex geometries on the surface of metallic materials.

• Journal of Technologic Dentistry
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• v.45 no.2
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• pp.31-38
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• 2023

Purpose: This in vitro study aimed to compare the trueness of 3-unit fixed dental provisional prostheses (FDPs) fabricated by three different additive manufacturing and subtractive manufacturing procedures. Methods: A reference model with a maxillary left second premolar and the second molar prepped and the first molar missing was scanned for the fabrication of 3-unit FDPs. An anatomically shaped 3-unit FDP was designed on computer-aided design software. 10 FDPs were fabricated by subtractive (MI group) and additive manufacturing (stereolithography: SL group, digital light processing: DL group, liquid crystal displays: LC group) methods, respectively (N=40). All FDPs were scanned and exported to the standard triangulated language file. A three-dimensional analysis program measured the discrepancy of the internal, margin, and pontic base area. As for the comparison among manufacturing procedures, the Kruskal-Wallis test and the Mann-Whitney test with Bonferroni correction were evaluated statistically. Results: Regarding the internal area, the root mean square (RMS) value of the 3-unit FDPs was the lowest in the MI group (31.79±6.39 ㎛) and the highest in the SL group (69.34±29.88 ㎛; p=0.001). In the marginal area, those of the 3-unit FDPs were the lowest in the LC group (25.39±4.36 ㎛) and the highest in the SL group (48.94±18.98 ㎛; p=0.001). In the pontic base area, those of the 3-unit FDPs were the lowest in the LC group (8.72±2.74 ㎛) and the highest in the DL group (20.75±2.03 ㎛; p=0.001). Conclusion: A statistically significant difference was observed in the RMS mean values of all the groups. However, in comparison to the subtractive manufacturing method, all measurement areas of 3-unit FDPs fabricated by three different additive manufacturing methods are within a clinically acceptable range.

• The Journal of Bigdata
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• v.6 no.2
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• pp.71-84
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• 2021

Since small and medium-sized enterprises fell short of the securement of technological competitiveness in the field of big data and artificial intelligence (AI) field-core technologies of the Fourth Industrial Revolution, it is important to strengthen the competitiveness of the overall industry through technology commercialization. In this study, we aimed to propose a priority related to technology transfer and commercialization for practical use of public research results. We utilized public research performance information, improving missing values of 6T classification by deep learning model with an ensemble method. Then, we conducted topic modeling to derive the converging fields of big data and AI. We classified the technology fields into four different segments in the technology portfolio based on technology activity and technology efficiency, estimating the potential of technology commercialization for those fields. We proposed a priority of technology commercialization for 10 detailed technology fields that require long-term investment. Through systematic analysis, active utilization of technology, and efficient technology transfer and commercialization can be promoted.

• Convergence Security Journal
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• v.22 no.5
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• pp.21-35
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• 2022

The use of digital information according to the development of information and communication technology and the 4th industrial revolution is continuously increasing and diversifying, and in proportion to this, crimes using digital information are also increasing. However, there are few cases of establishing an environment for processing and analysis of digital evidence in Korea. The budget allocated for each organization is different and the digital forensics laboratory built without solving the chronic problem of securing space has a problem in that there is no standard that can be referenced from the initial configuration stage. Based on this awareness of the problem, this thesis conducted an exploratory study focusing on tools and equipment necessary for building a digital forensics laboratory. As a research method, focus group interviews were conducted with 15 experts with extensive practical experience in the digital forensic laboratory or digital forensics field and experts' opinions were collected on the following 9 areas: network configuration, analyst computer, personal tools·equipment, imaging devices, dedicated software, open source software, common tools/equipment, accessories, and other considerations. As a result, a list of tools and equipment for digital forensic laboratories was derived.

• Convergence Security Journal
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• v.22 no.3
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• pp.25-32
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• 2022

Recently, the image processing industry has been activated as deep learning-based technology is introduced in the image recognition and detection field. With the development of deep learning technology, learning model vulnerabilities for adversarial attacks continue to be reported. However, studies on countermeasures against poisoning attacks that inject malicious data during learning are insufficient. The conventional countermeasure against poisoning attacks has a limitation in that it is necessary to perform a separate detection and removal operation by examining the training data each time. Therefore, in this paper, we propose a technique for reducing the attack success rate by applying modifications to the training data and inference data without a separate detection and removal process for the poison data. The One-shot kill poison attack, a clean label poison attack proposed in previous studies, was used as an attack model. The attack performance was confirmed by dividing it into a general attacker and an intelligent attacker according to the attacker's attack strategy. According to the experimental results, when the proposed defense mechanism is applied, the attack success rate can be reduced by up to 65% compared to the conventional method.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.861-866
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• 2023

Unlike conventional smart farms that require chemical fertilizers and large spaces, aquaponics farming, which utilizes the symbiotic relationship between aquatic organisms and crops to grow crops even in abnormal environments such as environmental pollution and climate change, is being actively researched. Different crops require different environments and nutrients for growth, so it is necessary to configure the ratio of aquatic organisms optimized for crop growth. This study proposes a method to measure the degree of growth based on area and volume using image processing techniques in an aquaponics environment. Tilapia, carp, catfish, and lettuce crops, which are aquatic organisms that produce organic matter through excrement, were tested in an aquaponics environment. Through 2D and 3D image analysis of lettuce and real-time data analysis, the growth degree was evaluated using the area and volume information of lettuce. The results of the experiment proved that it is possible to manage cultivation by utilizing the area and volume information of lettuce. It is expected that it will be possible to provide production prediction services to farmers by utilizing aquatic life and growth information. It will also be a starting point for solving problems in the changing agricultural environment.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.825-834
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• 2023

The demands of people who purchase fashion products on Internet shopping are gradually increasing, and attempts are being made to provide user-friendly images with 3D contents and web 3D software instead of pictures and videos of products provided. As a reason for this issue, which has emerged as the most important aspect in the fashion web shopping industry, complaints that the product is different when the product is received and the image at the time of purchase has been heightened. As a way to solve this problem, various image processing technologies have been introduced, but there is a limit to the quality of 2D images. In this study, we proposed an automatic conversion technology that converts 2D images into 3D and grafts them to web 3D technology that allows customers to identify products in various locations and reduces the cost and calculation time required for conversion. We developed a system that shoots a mannequin by placing it on a rotating turntable using only 8 cameras. In order to extract only the clothing part from the image taken by this system, markers are removed using U-net, and an algorithm that extracts only the clothing area by identifying the color feature information of the background area and mannequin area is proposed. Using this algorithm, the time taken to extract only the clothes area after taking an image is 2.25 seconds per image, and it takes a total of 144 seconds (2 minutes and 4 seconds) when taking 64 images of one piece of clothing. It can extract 3D objects with very good performance compared to the system.