• Journal of Dental Rehabilitation and Applied Science
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• v.38 no.4
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• pp.196-203
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• 2022

Purpose: This study aimed to evaluate the accuracy and clinical usability of an identification model using deep learning for 79 dental implant types. Materials and Methods: A total of 45396 implant fixture images were collected through panoramic radiographs of patients who received implant treatment from 2001 to 2020 at 30 dental clinics. The collected implant images were 79 types from 18 manufacturers. EfficientNet and Meta Pseudo Labels algorithms were used. For EfficientNet, EfficientNet-B0 and EfficientNet-B4 were used as submodels. For Meta Pseudo Labels, two models were applied according to the widen factor. Top 1 accuracy was measured for EfficientNet and top 1 and top 5 accuracy for Meta Pseudo Labels were measured. Results: EfficientNet-B0 and EfficientNet-B4 showed top 1 accuracy of 89.4. Meta Pseudo Labels 1 showed top 1 accuracy of 87.96, and Meta pseudo labels 2 with increased widen factor showed 88.35. In Top5 Accuracy, the score of Meta Pseudo Labels 1 was 97.90, which was 0.11% higher than 97.79 of Meta Pseudo Labels 2. Conclusion: All four deep learning algorithms used for implant identification in this study showed close to 90% accuracy. In order to increase the clinical applicability of deep learning for implant identification, it will be necessary to collect a wider amount of data and develop a fine-tuned algorithm for implant identification.

• Smart Media Journal
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• v.11 no.2
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• pp.77-83
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• 2022

The neuromorphic architecture uses a spiking neural network (SNN) model to derive more accurate results as more spike values are accumulated through inference experiments. When the inference result converges to a specific value, even if the inference experiment is further performed, the change in the result is smaller and power consumption may increase. In particular, in an AI-based IoT environment, power consumption can be a big problem. Therefore, in this paper, we propose a technique to reduce the power consumption of AI-based IoT by reducing the inference time by adjusting the inference image exposure time in the neuromorphic architecture environment. The proposed technique calculates the next inferred image exposure time by reflecting the change in inference accuracy. In addition, the rate of reflection of the change in inference accuracy can be adjusted with a coefficient value, and an optimal coefficient value is found through a comparison experiment of various coefficient values. In the proposed technique, the inference image exposure time corresponding to the target accuracy is greater than that of the linear technique, but the overall power consumption is less than that of the linear technique. As a result of measuring and evaluating the performance of the proposed method, it is confirmed that the inference experiment applying the proposed method can reduce the final exposure time by about 90% compared to the inference experiment applying the linear method.

• The Journal of Bigdata
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• v.6 no.2
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• pp.1-15
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• 2021

The unprecedented pandemic of infectious diseases called COVID-19 has dampened human and material movement, and changes in the global economic structure have caused various economic and industrial problems such as worsening employment along with the domestic and international economic recession. In this crisis situation, the government announced the "New Deal" as a new card to enhance economic vitality following the "emergency disaster support fund." This means that the first business of the Digital New Deal, the beginning and core of the New Deal, begins digital transformation from collecting data, which is the "rice" of digital transformation to the data dam. Until now, not only the government but also local governments have established and operated platforms for collecting and sharing public data by establishing various data portals. It is evaluated that it lacks utilization for commercialization as not only the government but also local governments focus only on building the platform without considering the business model when building the initial public data platforms. In particular, in the case of regions, there is a lack of public data to be used for data business, so it is necessary to utilize data from public institutions in the region. In this study, various data collection, data quality improvement, and data utilization improvement were suggested as measures to solve these problems.

• The Journal of Bigdata
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• v.7 no.2
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• pp.31-41
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• 2022

Steel is one of the most fundamental components to mechanical industry. However, the quality of products are greatly impacted by the surface defects in the steel. Thus, researchers pay attention to the need for surface defects detector and the deep learning methods are the current trend of object detector. There are still limitations and rooms for improvements, for example, related works focus on developing the models but don't take into account real-time application with practical implication on industrial settings. In this paper, a real-time application of steel surface defects detection based on YOLOv4 is proposed. Firstly, as the aim of this work to deploying model on real-time application, we studied related works on this field, particularly focusing on one-stage detector and YOLO algorithm, which is one of the most famous algorithm for real-time object detectors. Secondly, using pre-trained Yolov4-Darknet platform models and transfer learning, we trained and test on the hot rolled steel defects open-source dataset NEU-DET. In our study, we applied our application with 4 types of typical defects of a steel surface, namely patches, pitted surface, inclusion and scratches. Thirdly, we evaluated YOLOv4 trained model real-time performance to deploying our system with accuracy of 87.1 % mAP@0.5 and over 60 fps with GPU processing.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.597-603
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• 2023

The paradigm of military operations has evolved from platform-centric warfare to network-centric warfare and further to information-centric warfare, driven by advancements in information technology. In recent years, with the development of cutting-edge technologies such as big data, artificial intelligence, and the Internet of Things (IoT), military operations are transitioning towards knowledge-centric warfare (KCW), based on artificial intelligence. Consequently, the military places significant emphasis on integrating advanced information and communication technologies (ICT) to establish reliable C4I (Command, Control, Communication, Computer, Intelligence) systems. This research emphasizes the need to apply data mining techniques to analyze and evaluate various aspects of C4I systems, including enhancing combat capabilities, optimizing utilization in network-based environments, efficiently distributing information flow, facilitating smooth communication, and effectively implementing knowledge sharing. Data mining serves as a fundamental technology in modern big data analysis, and this study utilizes it to analyze real-world cases and propose practical strategies to maximize the efficiency of military command and control systems. The research outcomes are expected to provide valuable insights into the performance of C4I systems and reinforce knowledge-centric warfare in contemporary military operations.

• Information Systems Review
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• v.23 no.3
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• pp.51-75
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• 2021

Global e-commerce websites offer personalized recommendation services to gain sustainable competitiveness. Existing studies have offered personalized recommendation services using quantitative preferences such as ratings. However, offering personalized recommendation services using only quantitative data has raised the problem of decreasing recommendation performance. For example, a user gave a five-star rating but wrote a review that the user was unsatisfied with hotel service and cleanliness. In such cases, has problems where quantitative and qualitative preferences are inconsistent. Recently, a growing number of studies have considered review data simultaneously to improve the limitations of existing personalized recommendation service studies. Therefore, in this study, we identify review and rating mismatches and build a new user profile to offer personalized recommendation services. To this end, we use deep learning algorithms such as CNN, LSTM, CNN + LSTM, which have been widely used in sentiment analysis studies. And extract sentiment features from reviews and compare with quantitative preferences. To evaluate the performance of the proposed methodology in this study, we collect user preference information using real-world hotel data from the world's largest travel platform TripAdvisor. Experiments show that the proposed methodology in this study outperforms the existing other methodologies, using only existing quantitative preferences.

• The Journal of Korean Academy of Prosthodontics
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• v.51 no.4
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• pp.307-314
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• 2013

Purpose: The aim of this study was to evaluate the effect of immobilization of the recombinant human bone morphogenetic protein 2 (rhBMP-2) on anodized titaum implants coated with heparin to enhance the vertical alveolar ridge augmentation in the supraalveolar peri-implant defect region. Materials and methods: 18 pure titanium implants (7.0 mm in length, 3.5 mm in diameter) were manufactured for this study. All implants were anodized and designed insertion reference line marked with laser at the apical 2.5 mm from the fixture platform. Implantation of 6 noncoated anodized implants (Control group), 6 anodized implants physically adsorbed with rhBMP-2 by dip and dry method (BMP group) and 6 anodized implants chemically immobilized 3,4-dihydroxyphenylalanine (DOPA)-heparin/ rhBMP-2 (Hep-BMP group) was performed in the both mandibular of three male adult beagle dogs using split-mouth design. Radiologic examinations were performed immediately after implant placement and 4 and 8 weeks after implant placement. The amount of mesio-distal bone augmentation was evaluated by measuring the vertical distance from the platform to the marginal bone. Statistical analysis was performed using one-way analysis of variance (SPSS version 18.0) and multiple comparison analysis of The Kruskal-Wallis test and the Mann-Whitney U test. Statistical significance was established at the 5% significant level. Results: At the 4 weeks vertical alveolar ridge augmentation of Control group, BMP group and Hep-BMP group is $0.09{\pm}0.22mm$, $1.02{\pm}0.72mm$, and $1.29{\pm}0.51mm$, At the 8 weeks $0.11{\pm}1.26mm$, $1.11{\pm}0.58mm$, $1.59{\pm}0.79mm$ according to radiographic observations. The two experimental groups showed a significantly increasing in vertical bone height compared with the control group (P<.05). However, there is no significant difference between the BMP group and Hep-BMP group (P>.05). Conclusion: The rhBMP-2 coated implants were enhanced the vertical bone growth in the supraalveolar peri-implant defect area. However, there is no significant difference between chemically and physically coating method.

• Cartoon and Animation Studies
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• s.43
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• pp.47-75
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• 2016

This study has analyzed the history of the subcontract animation in Korea that began with Golden Bat of TBC Animation Division in 1966 to 1980s and shed the light on the history of subcontract animation that has been processed over 30 years in Korean animation. For this purpose, through the outlined status of subcontract animation, such as, production company, production status, scale of industry and so forth, the status of the OEM industry then has been checked and it links the solidified background of animation into subcontract production industry with the situation in time for analysis. In addition, on the basis of the foregoing, it is intended to broaden the horizon of the history of animation through the analysis on new search for facilitating the creative animation by overcoming the issues and limits generated by the subcontract animation industry. 1970s was the time that the national objective is to advance heavy-chemical industry and export-led economic growth. From the late 1970s, the animation has been spot lighted as the main-stream export industry through the overseas subcontract orders for animation. Expansion of the subcontract animation production has been influenced from the national policies on public culture, dispersion of color TV, facilitation of video production market and other media changes of the time that led the decline of animation audiences in theaters, and another cause would be in lack of platform of broadcasting companies that avoided the independent animation production for its economic theory. The subcontract animation industry may have the positive evaluation in the aspect of expanding the animation environment, such as, structuring of animation infra, development of new human resources and etc. However, the technology-incentive 'production'-oriented advancement has created distorted structure in advancing the professional human resources due to the absence of 'pre-production' of planning and others as well as the insufficient perception on 'post production (post work)', and it was unable to formulate domestic market by re-investing the capital accumulated for OEM industry into the production of creative animation and it has been assessed as negative aspect. Animation is a cultural and spiritual product of a country. Therefore, the systematic support policy for the facilitation of the creative animation, such as, development of professional human resources, creation of outstanding work, formation of market to make the pre-circulation structure and so forth has to be sought. However, animation is an industry, but there is no perception that it is a cultural industry based on the creativeness, not hardware-oriented manufacturing business. Such a lack of recognition, there was no policies to make the market and facilitate the creative animation by the animation of Korea for this period through the long-term plan and investment for independent work production. Such an attempt is newly begun through diverse searches for protection and advancement of creative animation in Korea after 1990s.

• Journal of the Korean Electrochemical Society
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• v.24 no.3
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• pp.65-75
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• 2021

Coin cell is a basic testing platform for battery research, discovering new materials and concepts, and contributing to fundamental research on next-generation batteries. Li metal batteries (LMBs) are promising since a high energy density (~500 Wh kg^-1) is deliverable far beyond Li-ion. However, Li dendrite-triggered volume fluctuation and high surface cause severe deterioration of performance. Given that such drawbacks are strongly dependent on the cell parameters and structure, such as the amount of electrolyte, Li thickness, and internal pressure, reliable Li metal coin cell testing is challenging. For the LMB-specialized coin cell testing platform, this study suggests the optimal coin cell structure that secures performance and reproducibility of LMBs under stringent conditions, such as lean electrolyte, high mass loading of NMC cathode, and thinner Li use. By controlling the cathode/anode (C/A) area ratio closer to 1.0, the inactive space was minimized, mitigating the cell degradation. The quantification and imaging of inner cell pressure elucidated that the uniformity of the pressure is a crucial matter to improving performance reliability. The LMB coin cells exhibit better cycling retention and reproducibility under higher (0.6 MPa → 2.13 MPa) and uniform (standard deviation: 0.43 → 0.16) stack pressure through the changes in internal parts and introducing a flexible polymer (PDMS) film.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.105-120
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• 2020

This study explores the process of the actual content production and distribution, by creating a YouTube channel to promote the popular music contents produced by the researcher, which thus reflects the reality where the production of video contents rapidly increases. A YouTube channel titled "Alida Music", of which the focus was to promote indie musicians, was created on February 2019. The contents of 10 indie musicians were produced in one-take live format. The information of the indie musicians was displayed in the form of a screen business card, with their e-mail address and SNS account at the top. Therefore, this promotional design was named "Card Live". Promotional video contents marked with the QR code in the lower right on the screen were produced, along with the promotional phrase "Communicate directly with the artist through the QR code", which allows viewers to watch other contents of the indie musician when they scan the QR code. This research conducted a study on how to improve and promote "Card Live" contents of "Alida Music", which were produced through this process. A group interview targeting five indie musicians, among whom one participant deemed significant was selected to conduct a one-to-one in-depth interview. As a result of the study, the following three conclusions were drawn. First, YouTube was found to be the medium with the greatest influence and highest efficiency at the lowest cost. Second, the evaluation of the participants on "Card Live" were divided into the three categories: need for one-take live, the design elements of "Card Live", and scanning issues of the QR code. Third, there is a need for promotional methods that can effectively utilize the media aspects of YouTube: the channel management issues such as raising public awareness as well as the number of subscribers of "Alida Music" should be resolved and measures to effectively use various media including other SNS should be developed. In terms of its content, it is imperative to recruit diverse performers to make various contents, as well as to come up with ways to link "Card Live" contents with offline. Based on these results, "Card Live" contents should be further revised and complemented in order to provide interesting contents to consumers, which will further develop "Alida Music" as a platform where various musicians and companies meet, thereby inducing contracts with popular music agencies and generating advertising revenues. However, since this study was carried out only with the limited number of participants, future studies should include more participants to bring forth a variety of promotional plans and improvement measures. Also, in the era of consuming contents through smart devices, the fact that some features of "Card Live" were available only on PC, did not fully reflect the characteristics of the times. In the future research, various contents that smartphone users can access and view freely without PC should be produced.